Carbon footprint accounting method considering full life cycle

Abstract

The invention relates to the technical field of carbon footprint management, in particular to a carbon footprint accounting method considering a whole life cycle, which comprises the following steps: analyzing life cycle path assessment influence and compressing to generate a path serial number sequence, reconstructing, assessing and transmitting identification abnormity according to serial numbers and reconstructing, identifying turning matching factors to obtain an adaptive set, and calculating a carbon footprint accounting result according to the adaptive set. And positioning heat loss inversion critical contrast monitoring to obtain accounting verification information, and collecting, layering and summarizing the carbon amount according to verification conversion. According to the method, through comprehensive utilization of flow path information, measurement of emission intensity and activeness and path screening are achieved, analysis of node carbon transfer characteristics is achieved, the accuracy of carbon flow judgment is improved, matching of operation sections and factor conditions is combined, identification and truncation of heat loss characteristics in an energy link are adopted, the reasonability of an inversion range is enhanced, and the accuracy of carbon flow judgment is improved. Through comparison of an emission monitoring result and energy input, verification of accounting data is enhanced, cross-level conversion and collection are combined, and consistency and integrity of carbon emission mapping are guaranteed.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of carbon footprint management, and particularly relates to a carbon footprint accounting method considering a whole life cycle. BACKGROUND

[0002] The technical field of carbon footprint management includes the whole process of quantifying, evaluating, recording and managing energy resource consumption and greenhouse gas emissions, and its core content is to systematically account and track the carbon emissions generated by products, services or activities in the whole life stage based on the life cycle assessment method, to combine environmental science, energy system engineering, information system and management science, to form a technical system covering carbon data collection, accounting modeling, statistical analysis and report generation by establishing an emission factor database, a life cycle inventory data collection mechanism, a carbon emission accounting model and a supporting software platform, and to be applied to multiple industries such as industrial manufacturing, transportation, construction engineering, power systems and consumer goods, to support enterprise carbon management, policy making, carbon trading and low-carbon product certification, etc., wherein the carbon footprint accounting method considering the whole life cycle refers to constructing a carbon emission inventory based on life cycle inventory data for the carbon emissions generated by products or systems in each life cycle stage such as raw material acquisition, production and manufacturing, transportation and distribution, use and maintenance, and scrap recycling, calculating the carbon emissions in each stage according to a unified boundary and functional unit through carbon emission factor matching and phased accounting method, and using life cycle boundary determination rules, system boundary expansion mechanism and emission intensity collection method in the accounting process to realize the standardization and collection of multi-stage carbon emission data, combining rule templates and emission accounting forms to generate carbon emission accounting documents for projects or products, and specifically involving life cycle database management, emission factor table maintenance and itemized accounting.

[0003] The traditional carbon footprint accounting technology accounts for carbon emissions based on life cycle inventory, and when multiple paths are parallel under complex process conditions, the boundary range is often unclear, resulting in repeated calculation or omission of some low-contribution paths, the carbon transfer relationship between nodes is not effectively identified according to the input-output difference, resulting in deviation, the average value is difficult to reflect the stage change due to the dependence of the running section factor on the average value, the thermal loss mutation in the energy transfer process is not identified, causing the inversion boundary to be fuzzy, the cross-level accounting is collected in a simple summation manner, resulting in inconsistent functional unit mapping, which may cause calculation result deviation in industrial manufacturing or energy systems, and reduce the reference value of carbon emission data in policy making and trading scenarios. SUMMARY

[0004] The present application relates to the technical field of carbon footprint management, and particularly relates to a carbon footprint accounting method considering a whole life cycle.

[0005] In order to achieve the above object, the present application adopts the following technical scheme: A carbon footprint accounting method considering the whole life cycle, comprising the following steps: S1: calling a life cycle path list, analyzing a process path structure, marking node energy consumption sources, emission species and path frequency, evaluating path emission intensity and activity according to the relationship between energy consumption and frequency, calculating path impact indicators, screening path compression objects and adjusting the nesting relationship, and generating a path number sequence; S2: according to the path number sequence, analyzing the difference between the input and output amounts of each node, evaluating the carbon transfer efficiency, combining the energy consumption sources and emission proportion difference, identifying abnormal node numbers, removing the corresponding paths and rebuilding the adjacent node connections, and generating a path reconstruction connection number set; S3: according to the path reconstruction connection number set, analyzing the node load change rate and the emission amount trend, identifying the turning section starting point, extracting the load control type, the emission species and the energy consumption structure, matching the carbon factor library conditions, and generating a carbon factor adaptation set; S4: calling the carbon factor adaptation set, analyzing the energy input and output structure between path sections, constructing a conversion section list, identifying the heat loss distribution characteristics and judging the inversion critical position, comparing the energy input before the critical position with the emission monitoring data, and generating carbon footprint accounting verification information; S5: according to the carbon footprint accounting verification information, analyzing the carbon factor level and unit type of each path node, evaluating the matching relationship between the emission amount and the functional unit, converting the carbon factor based on the unit conversion ratio, collecting the conversion results, summarizing the carbon value by level, and generating multi-layer carbon collection total data.

[0006] As a further scheme of the present application, the path number sequence includes path identification coding, compression node number, and nesting level sequence, the path reconstruction connection number set includes node connection pair information, pruned path topology structure, and connection path number mapping, the carbon factor adaptation set includes load section number, factor label matching result, and factor associated section number, the carbon footprint accounting verification information includes energy input structure before truncation, emission monitoring matching item, and inversion path section strength comparison index, and the multi-layer carbon collection total data includes converted path carbon emission value, structure level collection coding, and functional unit attribution relationship.

[0007] As a further scheme of the present application, the path number sequence acquisition step specifically comprises: S111: calling a life cycle path list, obtaining the process path structure formed by the accounting object in each life cycle stage, collecting the energy consumption source category and the corresponding emission species quantity of each node in each path, and statistically analyzing the frequency type of the path in the process network, and generating a path node feature mapping value; S112: According to the path node feature mapping value, the number of emission species in each path node and the path occurrence frequency are extracted, the emission intensity and the process activity are evaluated, the influence difference of the process path on the carbon footprint is judged, the path carbon offset difference value is calculated, and the path influence index value is obtained; S113: The path influence index value is called, the carbon offset degree of each path is compared, the process path compression object is screened, the structure relationship of the process nested structure is adjusted and the level is reconstructed, the mapping relationship between the path set number and the compression structure is established, and the path number sequence is generated.

[0008] As a further scheme of the present application, the path reconstruction connection number set acquisition step specifically comprises: S211: According to the path number sequence, the node number in each path is collected, the emission input quantity and the emission output quantity corresponding to the node are detected, the normalized processing and difference are made, the node energy consumption source type data is combined, and the node carbon transfer deviation value is generated; S212: The node carbon transfer deviation value is called, the emission input and output between the node pairs, the energy consumption source proportion and the emission proportion are extracted, the carbon transfer efficiency between the nodes is calculated, the carbon transfer efficiency difference index value of the node pair is calculated, the node number of the transfer efficiency anomaly is identified, and the carbon transfer abnormal node number set is established; S213: The carbon transfer abnormal node number set is called, the abnormal node number corresponding path is removed from the process network, and the remaining nodes after the removal are reconnected in sequence, the path reconstruction connection number set is established according to the node connection relationship of the adjusted path.

[0009] As a further scheme of the present application, the carbon factor adaptation set acquisition step specifically comprises: S311: According to the path reconstruction connection number set, the load change rate and the unit emission quantity of each running node in the path network are detected, the trend curves of the two data are calculated, the intersection points of the trend curves are identified, the path section number corresponding to the intersection points is extracted, and the turning section number set is generated; S312: The turning section number set is called, the load control type, the emission species combination and the energy consumption structure distribution in the turning section are extracted, each feature data in the section is normalized, and the turning section feature value set is generated; S313: According to the turning section feature value set, the corresponding condition field in the carbon factor library is matched to form a similarity value set, the carbon emission factor of the current turning section is judged, and the carbon factor adaptation set is established.

[0010] As a further scheme of the present application, the carbon footprint accounting verification information acquisition step specifically comprises: S411: calling the carbon factor adaptation set, collecting the energy input category and energy output composition of the path segment according to the path segment order in the connection number set, judging the difference combination type and transmission characteristics of the input and output between the path segments, structurally marking the conversion relationship, and establishing an energy conversion segment number list; S412: calling the energy conversion segment number list, identifying the energy consumption distribution type and heat loss conversion proportion characteristics of each segment in the list, evaluating the concentration degree of heat loss phenomenon in the transmission process, and judging the inversion critical position according to the heat loss conversion degree, and establishing a heat loss inversion critical position set; S413: according to the heat loss inversion critical position set, accumulating the energy input data before the inversion critical position and comparing with the recorded emission monitoring data, generating carbon footprint accounting verification information.

[0011] As a further scheme of the present application, the process of judging the inversion critical position according to the heat loss conversion degree is specifically: obtaining the heat loss conversion proportion characteristic value of each segment in the energy conversion segment number list, arranging all the heat loss conversion proportion characteristic values in path segment order, and taking the heat loss conversion proportion difference change rate of adjacent path segments as the judgment basis, identifying the path segment interval where the heat loss conversion proportion continuously increases and exceeds the judgment reference, and the judgment reference is a heat loss inversion critical judgment threshold value calculated based on the weighted average change rate of the heat loss conversion proportion of the whole path segment; The acquisition process of the heat loss inversion critical judgment threshold value is specifically: the heat loss conversion proportion characteristic value of each segment in the energy conversion segment number list is weighted with the unit energy consumption value of the corresponding path segment, and the weighted result is compared with the heat loss average value, the node position with the maximum deviation value and the continuously increasing change rate is extracted as the heat loss trend mutation reference point, and the heat loss conversion proportion change rate of the reference point is used as the heat loss inversion critical judgment threshold value.

[0012] As a further scheme of the present application, the acquisition step of the multi-layer carbon collection total amount data is specifically: S511: according to the carbon footprint accounting verification information, detecting the carbon factor hierarchical type and unit type corresponding to each path node, calculating the matching value of the node emission amount and the functional unit, pairing and mapping the emission amount and the functional unit information of the hierarchical node, and generating hierarchical node mapping data; S512: calling the hierarchical node mapping data, converting the carbon factor across the hierarchy based on the unit conversion ratio, calculating the carbon factor conversion value corresponding to each path segment, and obtaining a path segment conversion result set; S513: according to the path segment conversion result set, summarizing the carbon value of each path segment according to the structure hierarchy, calculating the carbon collection total amount in the hierarchical structure, collecting the summary data and classifying according to the hierarchy, and generating multi-layer carbon collection total amount data.

[0013] Compared with the prior art, the application has the advantages and positive effects that: In the application, by comprehensive utilization of the process path information, the measurement of the emission intensity and the activity and the path screening are realized, the analysis of the node carbon transmission characteristics improves the accuracy of the carbon flow judgment, the matching of the operation section and the factor condition is combined, the identification and truncation of the heat loss characteristics in the energy link are adopted, the rationality of the inversion range is enhanced, the comparison of the emission monitoring result and the energy input strengthens the verification of the accounting data, the cross-level conversion and collection are combined to ensure the consistency and integrity of the carbon emission mapping. BRIEF DESCRIPTION OF DRAWINGS

[0014] Figure 1 is a main step schematic diagram of the application; Figure 2 is a path number sequence acquisition flowchart of the application; Figure 3 is a path reconstruction connection number set acquisition flowchart of the application; Figure 4 is a carbon factor adaptation set acquisition flowchart of the application; Figure 5 is a carbon footprint accounting verification information acquisition flowchart of the application; Figure 6 is a multi-layer carbon collection total data acquisition flowchart of the application. DETAILED DESCRIPTION

[0015] In order to make the purpose, technical scheme and advantages of the application more clear, the application is further described in detail below in combination with the drawings and examples. It should be understood that the specific examples described herein are only used to explain the application and do not limit the application.

[0016] In the description of the application, it should be understood that the orientations or positional relationships indicated by the terms "length", "width", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer" and the like are based on the orientations or positional relationships shown in the drawings, and are only for the convenience of describing the application and simplifying the description, and therefore cannot be understood as indicating or implying that the devices or elements referred to must have a particular orientation, be constructed and operated in a particular orientation, and therefore cannot be understood as limiting the application. In addition, in the description of the application, the meaning of "a plurality of" is two or more, unless otherwise specifically limited.

[0017] Referring to Figure 1 The application provides a technical scheme: a carbon footprint accounting method considering the whole life cycle, comprising the following steps: S1: Call the life cycle path list, analyze the process path structure, mark the node energy consumption source, emission species and path frequency, evaluate the path emission intensity and activity according to the relationship between energy consumption and frequency, calculate the path influence index, screen the path compression object and adjust the nesting relationship, and generate the path number sequence; S2: According to the path number sequence, analyze the difference between the input and output of each node, evaluate the carbon transfer efficiency, combine the energy consumption source and the difference of emission proportion, identify the abnormal node number, remove the corresponding path and rebuild the connection of adjacent nodes, and generate the path reconstruction connection number set; S3: According to the path reconstruction connection number set, analyze the node load change rate and the trend of emission quantity, identify the turning section starting point, extract the load control type, emission species and energy consumption structure, match the carbon factor library condition, and generate the carbon factor adaptation set; S4: Call the carbon factor adaptation set, analyze the energy input and output structure between path sections, build the conversion section list, identify the heat loss distribution characteristics and judge the inversion critical position, summarize the energy input before the critical position and compare it with the emission monitoring data, and generate the carbon footprint accounting verification information; S5: According to the carbon footprint accounting verification information, analyze the carbon factor level and unit type of each path node, evaluate the matching relationship between emission and functional unit, convert the carbon factor based on unit conversion rate, collect the conversion results, summarize the carbon value by level, and generate multi-layer carbon collection total data.

[0018] The path number sequence includes path identification code, compressed node number and nesting level sequence, the path reconstruction connection number set includes node connection pair information, pruned path topology structure and connection path number mapping, the carbon factor adaptation set includes load section number, factor label matching result and factor associated section number, the carbon footprint accounting verification information includes energy input structure before truncation, emission monitoring matching item and inversion path section strength comparison index, and the multi-layer carbon collection total data includes converted path carbon emission value, structure level collection code and functional unit attribution relationship.

[0019] Please refer to Figure 2 The acquisition steps of the path number sequence are as follows: S111: Call the life cycle path list, get the process path structure formed by the accounting object in each life cycle stage, collect the energy consumption source category and corresponding emission species quantity of each node in each path, and count the occurrence frequency type of the path in the process network, and generate the path node feature mapping value; The accounting object is set to the life cycle carbon footprint of a certain factory producing lithium ion battery positive material (lithium iron phosphate), the life cycle path list is called, which includes the whole process from raw material acquisition, material production, battery assembly, use to waste disposal, the "lithium iron phosphate synthesis" process path structure in the "material production" stage is obtained, the process path includes multiple serial nodes, specifically including "precursor mixing", "solid phase reaction", "washing and drying", "sintering", "product packaging" and the like, each node has clear input and output materials and energy consumption, for example, the "sintering" node is the core energy consumption link in lithium iron phosphate synthesis, the node uses electricity and natural gas as energy consumption sources, these energy consumption sources correspond to emissions of carbon dioxide ( ), nitrogen oxides ( ) and the like, the "sintering" node energy consumption source category is collected as "electricity" and "natural gas", the corresponding emission species number is , that is, and , at the same time, the frequency of the "sintering" path in the whole "lithium iron phosphate synthesis" flow network is counted, it is found that the sintering step is a continuous production process, which appears times in each batch of material production, and in the whole process cycle, considering multiple batches of production, the frequency type statistical value of the path is times per week, all energy consumption source categories of each node, corresponding emission species number and path frequency type data are systematically recorded, for example, the "precursor mixing" node energy consumption source category is "electricity", the emission species number is ( ), the path frequency type is times per week, the "washing and drying" node energy consumption source category is "steam", the emission species number is ( ), the path frequency type is times per week, all these collected data are sorted and associated to generate path node feature mapping values for describing the unique attributes of each path node.

[0020] S112: According to the path node feature mapping value, the emission species number in each path node and the path frequency are extracted, the emission intensity and the process activity are evaluated, the influence difference of the process path on the carbon footprint is judged, and the formula is used: ; The path carbon offset difference value is calculated to obtain the path influence index value; Among them, is the path carbon offset difference value, which represents the carbon footprint influence difference of the th path relative to the reference path, To normalize the number of emission types, representing the number of the first emission type. The ratio of the number of emission types corresponding to energy consumption sources in a given path to the number of the largest emission type in all paths is obtained by dividing the number of emission types in that path by the number of the largest emission type in all paths. Let be the normalized path frequency, representing the th path. The ratio of the frequency of a path in the process network to the maximum frequency is obtained by dividing the number of times the path appears by the maximum frequency of paths in the process. Normalized emission intensity, representing the first The ratio of the carbon emission intensity of a path in a unit process to the maximum emission intensity of all paths in the life cycle network is obtained by dividing the original emission intensity by the maximum emission intensity. The activity level of the process indicates the activity level of the first... The activity level of a path in the process network can be calculated based on the operation frequency, activation frequency, or energy consumption event frequency of the nodes in the path. The normalized reference carbon footprint value represents the first... The carbon footprint value of a reference path is the proportion of the baseline carbon footprint value of all paths. It is calculated by dividing the reference carbon footprint value of that path by the maximum value among all reference carbon footprint values ​​of all paths. The path number index indicates the sequential numbering of the path within the lifecycle process network. Each independent path is used to distinguish the position and characteristics of different process paths within the path set; Based on the feature mapping values ​​of path nodes, the number of emission types and the frequency of path occurrence are extracted for each path node. Emission intensity and process activity are assessed to determine the differences in the impact of process paths on carbon footprint, using the following formula: ; Calculate the path carbon offset difference value, where, The path carbon offset difference value represents the first... The difference in carbon footprint impact of a path relative to a reference path measures the path's contribution to the overall carbon footprint across multiple dimensions. A higher value indicates a greater carbon emission shift and more volatile fluctuations along the path, meaning a more concentrated carbon risk within the network. To normalize the number of emission types, representing the number of the first emission type. The ratio of the number of emission types corresponding to energy consumption sources in a given path to the number of the largest emission type in all paths is obtained by dividing the number of emission types in that path by the number of the largest emission type in all paths. Let be the normalized path frequency, representing the th path. The ratio of the frequency of a path in the process network to the maximum frequency is obtained by dividing the number of times the path appears by the maximum frequency of paths in the process. Normalized emission intensity, representing the first The ratio of the carbon emission intensity of a path in a unit process to the maximum emission intensity of all paths in the life cycle network is obtained by dividing the original emission intensity by the maximum emission intensity. The activity level of the process indicates the activity level of the first... The activity level of a path in the process network is calculated based on the operation frequency, activation frequency, or energy consumption event frequency of the nodes in the path. The normalized reference carbon footprint value represents the first... The carbon footprint value of a reference path is the proportion of the baseline carbon footprint value of all paths. It is calculated by dividing the reference carbon footprint value of that path by the maximum value among all reference carbon footprint values ​​of all paths. The path number index indicates the sequential numbering of the path within the lifecycle process network. A single independent path is used to distinguish the position and characteristics of different process paths within the path set. In the formula, the numerator term... This represents the combined impact of emission diversity and process usage intensity on a pathway. The greater the variety of emissions and the higher the frequency of use, the greater the pathway's potential impact on its carbon footprint. The denominator term... The combined effect of emission intensity and system activity of a pathway is measured. Higher emission intensity and stronger process activity indicate a higher potential carbon emission risk. Dividing the two yields the relative weight of the pathway between emission potential and risk. Finally, the normalized reference carbon footprint value is subtracted. The absolute value is then used to calculate the path carbon offset difference. The calculation logic lies in accurately identifying highly sensitive pathways with abnormal carbon emission performance or significant contributions to the system's carbon footprint by comparing the deviation of actual emission potential and risk performance from a preset reference benchmark. This provides a quantitative basis for subsequent pathway optimization. For example, in the lithium iron phosphate production process, for pathway optimization... ("Sintering" path), path (Washing and Drying Path) (For the "product packaging" path) calculation, firstly, the number of emission types for each path is obtained from the path node feature mapping values. (Sintering) is species, path (Washing and drying) is species, path (Product packaging) is The number of species with the largest emissions across all pathways is Calculation path Normalized emission types and quantities ,path of , path of , second, the path frequency of occurrence is obtained, the path , path , path , the frequency of occurrence of each path is weekly , the maximum frequency is , therefore, the normalized path frequency of path , path of , path of , then, the emission intensity and process activity are evaluated, for the sintering path, the original carbon emission intensity of each product (for example: per kilogram of lithium iron phosphate) is kg equivalent / kg product, the maximum emission intensity in all paths is kg equivalent / kg product, therefore, the normalized emission intensity , the original carbon emission intensity of the washing and drying path is kg equivalent / kg product, the normalized emission intensity , the original carbon emission intensity of the product packaging path is kg equivalent / kg product, the normalized emission intensity , for the process activity , according to the frequency of operation, the number of times of activation and the frequency of energy consumption events of the nodes in the path, the process activity of the "sintering" path is set to , the "washing and drying" path is , and the "product packaging" path is , finally, the normalized reference carbon footprint value is obtained, the reference carbon footprint value is set according to the industry benchmark or historical optimal data, for the "sintering" path, the reference carbon footprint value is kg equivalent / kg product, the maximum value of the reference carbon value in all paths is kg equivalent / kg product, and the normalized reference carbon footprint value is , for the "washing and drying" path, the reference carbon footprint value is kg equivalent / kg product, and , for the "product packaging" path, the reference carbon footprint value is kg equivalent / kg product, and , the above parameter values are substituted into the formula for calculation; ​path the path carbon offset difference value of the sintering path is: ; path the path carbon offset difference value of the washing and drying path is: ; path the path carbon offset difference value of the product packaging path is: ; The path carbon offset difference value is an index for evaluating the offset strength of a certain process path in the system relative to the carbon emission reference value, which comprehensively measures the pulling effect of the path on the overall carbon footprint in multiple dimensions, including the complexity of the path structure (emission species), the path use intensity (occurrence frequency), the emission intensity (intensity), and the system action degree (activity). The higher the value, the greater the carbon emission offset of the path, the more intense the fluctuation, and the more concentrated the carbon risk in the network. This index can be used as an important criterion for path screening to assist in identifying high-sensitive path segments that have abnormal carbon emission performance or significant contribution to the system carbon footprint in the whole-process life cycle path, facilitating subsequent path compression, structure adjustment, and node optimization operations. The results show that the carbon offset difference value of the path is the highest, followed by the path , and the path is the lowest, indicating that the carbon emission fluctuation of the "product packaging" path is the most intense, and the carbon risk is the most concentrated, while the carbon emission performance of the "sintering" path is relatively stable. The carbon offset difference values of all paths together constitute the path impact index value.

[0021] S113: Call the path impact index value, compare the carbon offset degree of each path, screen the process path compression object, adjust the structure and reconstruct the level of the process nesting structure relationship, establish the mapping relationship between the path set number and the compression structure, and generate the path number sequence; The path impact index value is called, which includes the carbon offset difference value of each path. For example, the carbon offset difference value of the sintering path is , the carbon offset difference value of the washing and drying path is , and the carbon offset difference value of the product packaging path is The system sets a carbon offset difference value threshold, which is used to identify high-carbon risk paths. The threshold is set according to industry best practices and historical optimization experience, and is adjusted according to the enterprise's own emission reduction target. For example, if the enterprise's emission reduction target is to reach the international advanced level, the threshold can be set as the top The average offset difference value of the high-carbon emission path, if the emission reduction target of the enterprise is to achieve significant reduction on the basis of the existing, the threshold can be set as the average value of all path offset difference values plus a standard deviation, in this embodiment, the carbon offset difference value judgment threshold is set as , by screening and comparing the carbon offset degree of each path, the path with carbon offset difference value higher than or equal to is identified as a high-carbon risk path, which needs to be compressed and adjusted in structure, the product packaging path ( ) and the washing and drying path ( ) are identified as process path compression objects, and the sintering path ( ) is not used as a compression object, for the identified high-carbon risk path, the structure of the process nesting relationship is adjusted and the level is reconstructed, for example, in the product packaging link, the original process may contain multiple layers of nesting, such as “outer film making-film wrapping”, “box making-box packing”, “pallet bundling-warehousing” and other sub-processes, since the product packaging path is identified as a high-carbon risk path, the system will disassemble and reconstruct the sub-processes such as outer film making and box making, and explore the use of recyclable materials or lightweight packaging solutions, and adjust the original nested structure to a flat structure, for example, the “outer film making” and “box making” two nodes are optimized to one “environmentally friendly packaging integrated” node, by simplifying the dependency relationship between nodes to reduce its carbon footprint, for the washing and drying path, if it is inefficient and has high emissions, it can be replaced by a more efficient membrane separation technology, or integrated with the waste heat recovery system after sintering to reduce steam consumption, this reconstruction will change the series or parallel relationship between nodes in the original process, establish a mapping relationship between path set number and compression structure, for example, the original “product packaging path-number P003” is mapped to the new “environmentally friendly packaging integrated path-number P_NEW003”, and the original “washing and drying path-number P002” is mapped to the new “high-efficiency washing and drying path-number P_NEW002”, all the paths after screening and adjustment form a path number sequence.

[0022] Please refer to Figure 3 , the acquisition steps of the path reconstruction connection number set are as follows: S211: According to the path number sequence, collect the node numbers in each path, detect the emission input quantity and emission output quantity corresponding to the node, normalize and subtract, and combine the node energy consumption source type data to generate the node carbon transfer deviation value; According to the path number sequence, for example, the "sintering" node (number N001) and the "high-efficiency washing and drying" node (number N_NEW002) in the reconstructed "lithium iron phosphate synthesis" process are processed, the "sintering" node number N001 is collected, and the emission input quantity and the emission output quantity are detected, the emission input quantity refers to the total amount of the to-be-emitted substance transferred from the previous node to the current node or the total amount of the to-be-treated emission generated by the current node itself, for example, a large amount of flue gas (containing , , ) will be generated in the combustion process of the sintering furnace, these flue gases are the direct emission input of the sintering process itself, if it is assumed that the input is unit equivalent, after being treated in the furnace or subsequently, part of them will be emitted, and part of them may be captured or converted into other substances, for example, it is detected that the emission input quantity corresponding to the "sintering" node is kilograms equivalent, and the emission output quantity is kilograms equivalent, and the emission input quantity corresponding to the "high-efficiency washing and drying" node is kilograms equivalent, and the emission output quantity is kilograms equivalent, in order to compare, the input and output quantities are normalized, the maximum value normalization method is adopted, the maximum emission input quantity (of kilograms equivalent) and the maximum emission output quantity (of kilograms equivalent) in all nodes are taken as the reference, the emission input quantity of the "sintering" node is normalized to , the emission output quantity is normalized to , the emission input quantity of the "high-efficiency washing and drying" node is normalized to , and the emission output quantity is normalized to , then, the normalized input and output quantities are subtracted, and the carbon transfer deviation of the "sintering" node is calculated as , and the carbon transfer deviation of the "high-efficiency washing and drying" node is calculated as , at the same time, combined with the node energy source type data, for example, the main energy source types of the "sintering" node are "natural gas" and "electricity", and the main energy source type of the "high-efficiency washing and drying" node is "electricity", these energy source type data will be combined with the above carbon transfer deviation value to generate the node carbon transfer deviation value.

[0023] S212: Call the node carbon transfer bias value, extract the emission input and output between node pairs, energy source proportion and emission proportion, calculate the carbon transfer efficiency between nodes, use the formula: ; Calculate the carbon transfer efficiency difference index value of the node pair, identify the node number of abnormal transfer efficiency, and establish the carbon transfer abnormal node number set; Wherein, is the carbon transfer efficiency difference index value between node and node , which is calculated by the input-output difference and the energy consumption structure difference, is the normalized value of the emission input quantity of node , which is obtained by normalizing the maximum value of all emission inflow quantities of node in the path node set, is the normalized value of the emission output quantity of node , which is obtained by normalizing the maximum value of the emission outflow quantity released by node to the downstream path, is the normalized value of the energy consumption source proportion of node , which is obtained by normalizing the energy consumption source proportion in node and converting it according to the energy consumption dimension set, is the normalized value of the emission proportion of node , which is obtained by normalizing the emission type corresponding proportion in node and converting it according to the emission species set, is the normalized structure value of node in the energy consumption source dimension , which is obtained by normalizing the energy consumption proportion of node in the first energy consumption type relative to the maximum value of the dimension, is the normalized structure value of node in the energy consumption source dimension , which is obtained by normalizing the energy consumption proportion of node in the first energy consumption type relative to the maximum value of the dimension, is the index of the forward node in the path, which is used to identify the starting node in the carbon transfer direction, is the index of the backward node in the path, which is used to identify the target node in the carbon transfer direction, is the index number of the energy consumption source dimension, which is used to represent the first energy consumption category in the node structure, The upper limit of the index for the total number of energy source dimensions, representing the total number of all energy categories contained in the node's energy consumption structure, and the upper limit of the average operation used to normalize the structure difference; By calling the node carbon transfer deviation value, extracting the emission input and output, energy source ratio and emission ratio between node pairs, and calculating the carbon transfer efficiency between nodes using the following formula: ; Calculate the carbon transfer efficiency difference index value of node pairs, where, For nodes With nodes The carbon transfer efficiency difference index between nodes is calculated by combining the input-output difference and the energy consumption structure difference. It represents the normalized offset strength of the carbon flow input and output between the two nodes and the comprehensive deviation of the distribution consistency under the multi-energy consumption structure. When this value is large, it means that there is a significant imbalance or structural distribution difference in the carbon flow transfer process between the corresponding nodes. Such nodes are more likely to become anomalies, risk links or optimization targets in the carbon footprint network. For nodes The normalized value of the emission input quantity, through the node The received emission inflows are normalized based on the maximum value within the path node set. For nodes The normalized value of the emission output quantity, through the node The amount of emissions released downstream is obtained by normalizing the output based on the maximum value within the set of path nodes. For nodes The normalized value of the proportion of energy consumption sources, obtained through statistical nodes. The proportion of each energy consumption source in the data was obtained by normalizing the data according to the energy consumption dimension set. For nodes The normalized value of the emission ratio, obtained through statistical nodes. The corresponding proportions of emission types are obtained by normalizing the emission type set. For nodes In terms of energy sources Normalized structure values ​​on the nodes In the The energy consumption ratio under each energy consumption type is obtained by normalizing it relative to the maximum value of the dimension. For nodes In terms of energy sources Normalized structure values ​​on the nodes In the The energy consumption ratio under each energy consumption type is obtained by normalizing it relative to the maximum value of the dimension. This is the index of the forward nodes in the path, used to identify the starting node in the direction of carbon transport. This is the index of the backward nodes in the path, used to identify the target node in the direction of carbon transport. The index number is used to represent the specific node in the energy source dimension. Energy consumption categories The upper limit of the index for the total number of energy source dimensions represents the total number of all energy categories contained in the node's energy consumption structure. It is used to normalize the average operational upper limit of the structure difference. The advantage of this formula is that it not only considers the input-output balance of carbon emissions between nodes, but also... The term reflects the net shift in carbon flow, also through the denominator. The project incorporates the density impact of nodal energy consumption structure and emission type, making the assessment more comprehensive. Furthermore, through the second part... This further quantifies the differences between two nodes in terms of various energy sources (such as electricity, natural gas, and steam). The greater the difference, the more significant the potential differences in energy utilization patterns or emission reduction potential between the two nodes. By considering these factors, the formula can more accurately identify node pairs with abnormal carbon transfer efficiency in the process, thereby focusing on risky links and guiding optimization. For example, in the lithium iron phosphate production process, considering the sintering node (node...) ) and subsequent high-efficiency washing and drying nodes (nodes) Carbon transfer efficiency between nodes Normalized values ​​of emission inputs ,node Normalized value of emissions output Regarding the proportion of energy consumption sources, nodes The energy sources for (sintering) are natural gas and electricity, assuming natural gas accounts for a certain percentage. Electricity share The largest proportion of energy consumption sources for all nodes is Therefore, node Normalized value of the proportion of energy consumption sources ,node (High-efficiency washing and drying) Energy consumption comes from electricity, accounting for [percentage missing]. After normalization, it becomes Normalized values ​​of the proportion of energy consumption sources for all nodes The maximum value is ,therefore, Normalization Regarding emission ratios, nodes The main emissions are and Assuming percentage , percentage ,node The main emissions of the node are , and the maximum proportion of the corresponding proportion of all node emission types is Therefore, the normalized value of the emission proportion of the node is , the normalized value of the emission proportion of the node is , and the maximum value of the normalized value of the corresponding proportion of all node emission types is Therefore, , The normalized value of the normalized value of the corresponding proportion of all node emission types is For the energy consumption source dimension , suppose there are energy consumption source dimensions, i.e., natural gas and electricity, the normalized structure value of the node on the natural gas dimension is , the normalized structure value on the electricity dimension is , the normalized structure value of the node on the natural gas dimension is , and the normalized structure value on the electricity dimension is Substitute the above parameters into the formula to calculate the carbon transfer efficiency difference index value of the node pair : ; ; ; ; ; The carbon transfer efficiency difference index value is an important dimensionless value for measuring the balance and consistency of node pairs in the carbon emission transfer process in the path network, representing the normalized deviation strength of carbon flow input and output between two nodes and the comprehensive deviation of distribution consistency under multi-energy consumption structure. When the value is larger, it means that there is significant imbalance or structural distribution difference in the carbon flow transfer process of the corresponding node pair, and such node is more likely to become an abnormal point, a risk link or an optimization target of the carbon footprint network; when the value is less than a preset threshold, it is considered that the transfer efficiency is at a normal level, and the node connection can be reserved. Therefore, the carbon transfer efficiency difference index value directly determines the screening standard of abnormal nodes and paths in the network, and is the core judgment basis for subsequent path elimination and structure reconstruction operation, which is helpful to realize the health management and risk focusing of the carbon emission flow network. The system sets a carbon transfer efficiency difference index value threshold, which is used to determine whether the carbon transfer efficiency of the node pair is abnormal. The threshold is set in reference to historical data analysis, expert experience and industry standards. For example, by statistically analyzing the carbon transfer efficiency difference index values of all node pairs in the past year, the mean and standard deviation are calculated, and the threshold is set to the mean plus times the standard deviation. In this embodiment, the threshold is set to When the carbon transfer efficiency difference index value is greater than or equal to the threshold , it is determined that the transfer efficiency is abnormal. The result shows that the carbon transfer efficiency difference index value between the sintering node and the high-efficiency washing and drying node is , which is higher than the preset threshold . Therefore, this node pair is identified as a transfer efficiency abnormality, and a carbon transfer abnormal node number set is established, which contains the number of node (sintering node) and node (high-efficiency washing and drying node).

[0024] S213: Call the carbon transfer abnormal node number set, remove the abnormal node number corresponding path from the flow network, and reestablish the sequential connection of the remaining nodes after elimination. According to the node connection relationship of the adjusted path, a path reconstruction connection number set is established. The carbon transfer abnormal node number set is called, for example, a number containing a sintering node (number N001) and a high-efficiency washing and drying node (number N NEW002), and the path corresponding to these abnormal node numbers is removed from the lithium iron phosphate production process network. Specifically, if the carbon transfer efficiency between the sintering node and the high-efficiency washing and drying node is abnormal, it indicates that there is a high carbon risk in the direct connection or interaction between the two nodes, and intervention is required. The original path segment from the sintering node to the high-efficiency washing and drying node is removed. After removal, the remaining nodes in the process network, for example, after the precursor mixing node (number N000), the original direct connection of the sintering node is removed, and the high-efficiency washing and drying node is subsequently connected to the product packaging node (number P NEW003). After removing the nodes, the sequential connection of the remaining nodes after removal is re-established. For example, if the sintering node is identified as abnormal and removed, the connection from its upstream node (e.g., the "precursor mixing" node) to its downstream node (e.g., the "washing and drying" node or the "waste heat recovery" system) needs to be re-evaluated. If the sintering process is optimized to a cleaner alternative process, the upstream node will be connected to a new alternative process node, or if two adjacent abnormal nodes are removed, their upstream node will be directly connected to the upstream neighbor of the downstream node, forming a new path. For example, the precursor mixing node is no longer connected to the sintering node, but is directly connected to a new "low-carbon solid-phase reaction" node, while the high-efficiency washing and drying node is now directly connected to the product packaging node. According to the node connection relationship of the adjusted path, a path reconstruction connection number set is established, which contains all the adjusted and reconnected path segments and their corresponding numbers, ensuring the logical integrity and traceability of the entire production process.

[0025] See Figure 4 The carbon factor adaptation set is obtained by the following steps: S311: According to the path reconstruction connection number set, detect the load change rate and unit emission quantity of each running node in the path network, calculate the trend curves of the two data, identify the intersection of the trend curves, extract the path segment number corresponding to the intersection, and generate a set of turning segment numbers; According to the path reconstruction connection number set, for example, a reconstructed path of the sintering section in the lithium iron phosphate production process, which contains nodes such as "pretreatment", "low-carbon sintering furnace operation" and "waste heat recovery", detect the load change rate and unit emission quantity of the "low-carbon sintering furnace operation" node in the path network. The load change rate refers to the change amplitude of the temperature, pressure or feed rate in the furnace per unit time, for example, the temperature increases by 10°C per minute The unit emission quantity refers to the amount of equivalent produced per kilogram of lithium iron phosphate produced under certain load conditions , for example, 0.1 kg of equivalent is produced per kilogram of product When the load change rate and unit emission quantity of the "low-carbon sintering furnace operation" node are detected, the trend curves of the two data are calculated, and the intersection of the trend curves is identified. The path segment number corresponding to the intersection is extracted, and a set of turning segment numbers is generated. kilogram Equivalent data are obtained through real-time sensor monitoring and historical data analysis, for example, in Within the capacity range of tons / day, the load change rate of the low-carbon sintering furnace is from arrive (Dimensionless, indicating relative change), the quantity of emissions per unit ranges from... arrive kilogram For equivalent / kilogram products, curve fitting is performed on these two data points to calculate their trend curves. For example, there may be a non-linear relationship between the rate of change of load and the quantity of emissions per unit, initially decreasing and then increasing. The intersection of the trend curves is identified; this intersection represents a critical point where the trends of the rate of change of load and the quantity of emissions per unit change significantly reverse. For instance, when the rate of change of load reaches a certain value, the growth rate of emissions per unit may change from a slow increase to a rapid increase, or from a decrease to an increase. This intersection may occur when the rate of change of load is... At that time, the corresponding unit emission quantity was kilogram For equivalent per kilogram of product, extract the path segment number corresponding to the intersection point. For example, in the "Low-carbon sintering furnace operation" node, the load change rate is... arrive The interval between operations is marked as a transition segment, and a set of transition segment numbers is generated, which contains the unique identifiers of all identified transition segments.

[0026] S312: Call the transition section number set, extract the load control type, emission item type combination and energy consumption structure distribution within the transition section, normalize each feature data within the section, and generate the transition section feature value set. Retrieve the set of transition segment numbers, for example, from this set to obtain a specific transition segment (number TS001) for the "Low-carbon Sintering Furnace Operation" node, which corresponds to the load change rate at... arrive Between, the amount of emissions per unit is arrive kilogram The operating range of the equivalent / kilogram product is used to extract the load control type, emission item combination, and energy consumption structure distribution within this transition zone. The load control type refers to the control strategy employed within this zone, such as "constant temperature and pressure control" or "segmented variable temperature control." The emission item combination refers to the specific types and proportions of emissions generated within this zone, for example... occupy , occupy Energy consumption structure distribution refers to the proportion of consumption from different energy sources (such as electricity and natural gas) within a given area. For example, electricity accounts for... Natural gas accounts for Each feature data point within the segment is normalized. For example, for load control types, it can be quantized into discrete values, such as "constant temperature and pressure control" being quantized as... "Segmented temperature control" is quantified as Normalization is performed based on the maximum value. For combinations of emission item types, percentage Normalization , percentage Normalization The proportion of electricity in the energy consumption structure distribution Normalization Natural gas percentage Normalization All the feature data after quantization and normalization together form the feature value set of the transition section.

[0027] S313: Based on the feature value set of the transition segment, a similarity value set is formed by matching it with the corresponding condition fields in the carbon factor library, the carbon emission factor of the current transition segment is determined, and a carbon factor fitting set is established. Based on the characteristic value set of the transition section, which includes the normalized value of the load control type for a specific transition section of the "low-carbon sintering furnace operation" node (e.g., ), and the normalized value of the combination of emission item categories (e.g. ) and normalized values ​​of energy consumption structure distribution (e.g., electricity: ,natural gas: By matching the data with corresponding condition fields in the carbon factor library, a pre-built database containing a large amount of carbon emission factor data under different process conditions, energy consumption types, emission types, and load modes, each carbon factor record has its corresponding condition field description. For example, a carbon factor might correspond to "electrolytic aluminum production, constant current control," Main emissions The condition for "electricity consumption" involves performing multi-dimensional similarity calculations between the fields of the feature value set of the transition zone and the condition fields in the carbon factor library. For example, variations of cosine similarity or Euclidean distance are used to evaluate the degree of matching in three dimensions: load control type, emission item category combination, and energy consumption structure distribution. For instance, if a record in the carbon factor library has an energy consumption structure distribution of electricity... ,natural gas The energy consumption structure distribution in the current transition zone (electricity) ,natural gas Similarity calculations are performed to obtain a high similarity value. All matching results together form a similarity value set, which contains the similarity score between each carbon factor database record and the current transition segment. Based on the similarity value set, the carbon emission factor of the current transition segment is determined, and the matching with the highest similarity or higher than a preset matching threshold (e.g., ...) is selected. The threshold is set based on historical data fit, expert evaluation, and industry benchmarks to ensure that the selected carbon factors accurately represent actual emissions. If multiple carbon factors have similarity scores higher than the threshold, a weighted average or expert evaluation can be used to select the final suitable factor. For example, the carbon emission factor in the carbon factor library that best matches the characteristics of this transitional period can be selected. kilogram Based on the equivalent / kilowatt-hour of electricity, a carbon factor adaptation set is established, which includes all transition segments and their corresponding adaptation carbon emission factors.

[0028] Please see Figure 5 The specific steps for obtaining carbon footprint verification information are as follows: S411: Call the carbon factor adaptation set, collect the energy input types and energy output composition of the path segments according to the path segment order in the connection number set, determine the difference combination type and transmission characteristics of input and output between path segments, perform structural marking on the conversion relationship, and establish a list of energy conversion segment numbers. The carbon factor adaptation set is invoked, which includes the carbon factor for the transition section of the "Low-carbon Sintering Furnace Operation" node. kilogram Electricity quantity / kWh, based on the path segment order within the path reconstruction connection number set, for example, "preprocessing" (path segment P01) - "Low-carbon sintering furnace operation" (path segment P02) - "Waste heat recovery" (path segment P03) - "High-efficiency washing and drying" (path segment P04) collects the energy input types and energy output composition for each path segment. For path segment P02 "Low-carbon sintering furnace operation", its energy input types include electricity (e.g., ... kilowatt-hours) and natural gas (e.g.) cubic meters), energy output components include thermal energy (e.g. Megajoules), waste heat steam (e.g.) tons) and a small amount of electricity (e.g. (UKWh, through combined heat and power), determine the difference in input and output combination types and transmission characteristics between path segments. For example, the energy input of path segment P02 is multiple energy types, and the output is multiple types of energy (heat, steam, electricity). This belongs to the complex energy conversion type of "multiple inputs-multiple outputs". Its transmission characteristics include energy efficiency, energy quality changes and energy carrier conversion. The conversion relationship is structurally marked. For example, path segment P02 is marked as an "energy comprehensive utilization type" conversion segment, and its specific parameters such as electricity-heat energy conversion efficiency and natural gas-heat energy conversion efficiency are recorded. All energy conversion segments that have been structurally marked jointly establish an energy conversion segment number list, which contains the unique number of each energy conversion segment and its detailed energy conversion characteristic description.

[0029] S412: Call the list of energy conversion segment numbers, identify the energy consumption distribution type and heat loss conversion ratio characteristics of each segment in the list, assess the degree of heat loss concentration during the transfer process, and determine the inversion critical position based on the degree of heat loss conversion, and establish a set of heat loss inversion critical positions. The energy conversion segment number list is retrieved, and the energy consumption distribution type and heat loss conversion ratio characteristics of each segment in the list are identified. For example, in the lithium iron phosphate production process, the energy conversion segment list contains four main segments: P01 "Pretreatment", P02 "Low-carbon sintering furnace operation", P03 "Waste heat recovery", and P04 "High-efficiency washing and drying". For the P02 "Low-carbon sintering furnace operation" segment, its energy consumption distribution type is "gas-electric composite", and its heat loss conversion ratio characteristic value is... (Right now (The input energy is lost in the form of heat loss). For the P03 "waste heat recovery" section, its energy consumption distribution type is "waste heat utilization type", and the characteristic value of the heat loss conversion ratio is... Assess the concentration of heat loss during the transfer process and arrange all heat loss conversion ratio characteristic values ​​in the order of path segments. For example, P01 is... P02 is P03 is P04 is The critical inversion position is determined based on the degree of heat loss conversion. Specifically, the characteristic value of the heat loss conversion ratio for each segment is obtained. For example, P01 to P04 are respectively... , , , Based on the rate of change of the difference in heat loss conversion ratio between adjacent path segments, the system identifies path segment intervals where the heat loss conversion ratio continuously increases and exceeds the judgment benchmark. First, it calculates the critical judgment threshold for heat loss inversion, and then numerically weights the characteristic value of the heat loss conversion ratio of each segment with its corresponding unit energy consumption value. For example, the unit energy consumption of P01 is... Unit, P02 unit energy consumption is Unit, P03 unit energy consumption is Unit, P04 unit energy consumption is Units, weighted result: P01: P02: P03: P04: The average heat loss of all path segments is calculated as follows: ,Right now The weighted results are compared with the mean heat loss, and the node with the largest offset and a continuously increasing rate of change is extracted as the reference point for abrupt changes in the heat loss trend. For example, the heat loss conversion ratio from P01 to P02 is... Increase to Things have changed. From P02 to P03 Reduce to From P03 to P04 Reduce to The offset value is the largest ( And the rate of change increases continuously (in this example, only P01 to P02 shows an increasing trend). Therefore, the P02 node position is extracted as the reference point for the abrupt change in heat loss trend, and the rate of change of the heat loss conversion ratio at the reference point P02 is used. As the critical threshold for heat loss inversion, we return to the step of determining the critical inversion position, identifying the path segment interval where the heat loss conversion ratio continuously increases and exceeds the judgment benchmark, and comparing the rate of change of the difference in heat loss conversion ratio between adjacent path segments: the rate of change of the difference between P01 and P02 is... The rate of change of the difference between P02 and P03 is The rate of change of the difference between P03 and P04 is Due to the rate of change of the heat loss conversion ratio difference between P01 and P02 Exceeding the judgment threshold (The rate of change of the reference point for the sudden change in heat loss trend), and P01 and P02 are continuously increasing. Therefore, node P02 is identified as the critical position for inversion, and a set of critical positions for heat loss inversion is established, which includes the number of node P02.

[0030] Table 1: Heat loss and energy consumption data of the energy conversion section in the lithium iron phosphate production process ; Table 1 lists the characteristic values ​​of heat loss conversion ratio and unit energy consumption value of each energy conversion stage in the lithium iron phosphate production process.

[0031] S413: Based on the set of critical positions retrieved by heat loss, accumulate the energy input data before the critical positions and compare it with the recorded emission monitoring data to generate carbon footprint accounting verification information; Based on the heat loss inversion critical position set, which includes the P02 "Low-carbon sintering furnace operation" node, the energy input data before the inversion critical position is accumulated, that is, the energy input data of the P01 "preprocessing" path segment is accumulated. For example, the total energy input of P01 is... The electricity generated in kilowatt-hours corresponds to a certain amount of carbon emissions during its use, and this is compared with recorded emissions monitoring data. For example, in the P01 "pretreatment" section, the actual carbon emissions monitored by real-time sensors are... kilogram Equivalent, and based on the energy input of that segment ( (kilowatt-hours of electricity) and a suitable carbon factor (e.g., the amount of electricity generated per kilowatt-hour of electricity) and the appropriate carbon factor (e.g., the amount of electricity generated per kilowatt-hour of electricity). kilogram (equivalent), the theoretical carbon emissions calculated are kilogram Equivalents are used to generate carbon footprint accounting verification information by comparing theoretical calculations with actual monitoring values. For example, in this case, the theoretical calculations and actual monitoring values ​​are in perfect agreement, indicating that the carbon footprint accounting results before the inversion critical position are highly accurate, providing strong support for subsequent accounting results.

[0032] Please see Figure 6 The specific steps for obtaining total carbon aggregation data at multiple levels are as follows: S511: Based on the carbon footprint accounting verification information, detect the carbon factor hierarchical type and unit type corresponding to each path node, calculate the matching value between node emissions and functional units, pair and map the emissions and functional unit information of hierarchical nodes, and generate hierarchical node mapping data. Based on carbon footprint accounting verification information, the accuracy of the accounting results was confirmed. The carbon factor level type and unit type corresponding to each path node were examined. For example, in the lithium iron phosphate production process, the carbon factor level type corresponding to the "precursor mixing" node (number N000) is "raw material processing level," and its functional unit is "per ton of precursor." Meanwhile, the carbon factor level type corresponding to the "low-carbon sintering furnace operation" node (number P02) is "core production process level," and its functional unit is "per kilogram of lithium iron phosphate product." The matching value between node emissions and functional units was calculated. For example, for the "precursor mixing" node, its emissions are... kilogram Equivalents per ton of precursor, its functional unit is "per ton of precursor", and the matching value is... For the "low-carbon sintering furnace operation" node, the emissions are: kilogram The equivalent per kilogram of lithium iron phosphate product, whose functional unit is "per kilogram of lithium iron phosphate product", has a matching value of The emission levels and functional unit information of the hierarchical nodes are paired and mapped. For example, the "precursor mixing" node is mapped to "raw material processing level". kilogram (equivalent / ton precursor), mapping the "low-carbon sintering furnace operation" node to ("core production process level"). kilogram (Equivalent / kg lithium iron phosphate product), all these pairing mapping information together generate hierarchical node mapping data.

[0033] S512: Call the hierarchical node mapping data, convert the carbon factor across levels based on the unit conversion ratio, calculate the carbon factor conversion value corresponding to each path segment, and obtain the path segment conversion result set; Call the hierarchical node mapping data, which includes the mapping of the "precursor mixing" node ("raw material processing hierarchy"). kilogram The mapping between the equivalent amount / ton of precursor and the "low-carbon sintering furnace operation" node ("core production process level") kilogram (Equivalent per kilogram of lithium iron phosphate product), based on a unit conversion ratio, converts carbon factors across levels. For example, if the functional unit of the final product is "per kilogram of lithium iron phosphate product," the carbon emissions of the "raw material processing level" (in "per ton of precursor") need to be converted into equivalent emissions of "per kilogram of lithium iron phosphate product." Assuming production... Kilograms of lithium iron phosphate products require For kilograms of precursor, the unit conversion ratio is: For kilograms of precursor / kilograms of lithium iron phosphate product, the emissions equivalent to the "precursor mixing" node per kilogram of lithium iron phosphate product functional unit are: kilogram Equivalent / ton precursor ( (kg precursor / kg lithium iron phosphate product) ( ton / kilograms) = kilogram The functional unit of the "low-carbon sintering furnace operation" node is itself "per kilogram of lithium iron phosphate product," therefore its carbon factor conversion value is directly [value missing]. kilogram The carbon factor conversion value is calculated for each path segment based on the equivalent of one kilogram of lithium iron phosphate product. All calculated conversion values ​​are used to obtain the path segment conversion result set. This result set ensures that all carbon emission data are compared and accumulated under a unified functional unit.

[0034] S513: Based on the path segment conversion result set, summarize the carbon value of each path segment according to the structural level, calculate the total carbon collection within the hierarchical structure, collect and summarize the data and classify and number it according to the level to generate multi-level carbon collection total data. Based on the path segment conversion result set, which includes the converted value of the "precursor mixing" path segment, kilogram The equivalent value per kilogram of lithium iron phosphate product, converted to the "low-carbon sintering furnace operation" path segment is: kilogram For lithium iron phosphate products in equivalent weight per kilogram, the carbon value of each pathway segment is summarized according to structural level. For example, the "precursor mixing" pathway segment is classified into the "raw material processing level," and the "low-carbon sintering furnace operation" pathway segment is classified into the "core production process level." If the "raw material processing level" includes other pathway segments, such as the "lithium source extraction" pathway segment, the converted value is... kilogram For equivalent / kg lithium iron phosphate products, the total carbon collection within the "raw material processing level" is calculated as follows: kilogram For lithium iron phosphate products in equivalent weight per kilogram, if the "core production process level" also includes the "washing and drying" path segment, the converted value is... kilogram For equivalent / kg lithium iron phosphate products, the total carbon collection within the "core production process level" is calculated as follows: kilogram For lithium iron phosphate products in equivalent quantities per kilogram, these aggregated data are collected and categorized by level, for example, the "raw material processing level" is numbered CL01, and its total quantity is... kilogram For product equivalents per kilogram, the "core production process level" is numbered CL02, and its total quantity is... kilogram Equivalent per kilogram of product, the aggregated data from all levels together generate multi-level total carbon collection data, which clearly shows the carbon footprint contribution of the product at different life cycle levels.

[0035] The above are merely preferred embodiments of the present invention and are not intended to limit the present invention in any other way. Any person skilled in the art may make changes or modifications to the above-disclosed technical content to create equivalent embodiments that can be applied to other fields. However, any simple modifications, equivalent changes, and modifications made to the above embodiments based on the technical essence of the present invention without departing from the scope of the present invention shall still fall within the protection scope of the present invention.

Claims

1. A carbon footprint accounting method considering the entire life cycle, characterized in that, Includes the following steps: S1: Call the lifecycle path list, analyze the process path structure, mark the energy consumption source, emission type and path frequency of the node, evaluate the emission intensity and activity of the path based on the relationship between energy consumption and frequency, calculate the path impact index, screen path compression objects and adjust the nesting relationship, and generate the path number sequence. S2: Based on the path number sequence, analyze the difference between the input and output of emissions at each node, evaluate the carbon transfer efficiency, and identify abnormal node numbers by combining the differences in energy consumption sources and emission ratios, remove the corresponding paths and reconstruct the connections between adjacent nodes to generate a path reconstruction connection number set. S3: Reconstruct the connection number set according to the path, analyze the node load change rate and emission quantity trend, identify the starting point of the turning section, extract the load control type, emission type and energy consumption structure, match the carbon factor library conditions, and generate a carbon factor adaptation set. S4: Call the carbon factor adaptation set, analyze the energy input and output structure between path segments, construct a list of conversion segments, identify the heat loss distribution characteristics and determine the inversion critical position, summarize the energy input before the critical position and compare it with the emission monitoring data to generate carbon footprint accounting verification information.

2. The carbon footprint accounting method considering the entire life cycle according to claim 1, characterized in that, The path numbering sequence includes path identifier encoding, compressed node number, and nested hierarchical order. The path reconstruction connection number set includes node connection pair information, pruned path topology, and connection path number mapping. The carbon factor adaptation set includes load segment number, factor label matching result, and factor associated segment number. The carbon footprint accounting verification information includes energy input structure before truncation, emission monitoring matching items, and inverted path segment intensity comparison index.

3. The carbon footprint accounting method considering the entire life cycle according to claim 1, characterized in that, The specific steps for obtaining the path number sequence are as follows: S111: Call the lifecycle path list to obtain the process path structure formed by the accounting object in each lifecycle stage, collect the energy source category and corresponding emission type and quantity of each node in each path, and count the frequency of the path in the process network to generate path node feature mapping values. S112: Based on the path node feature mapping value, extract the number of emission types and the frequency of path occurrence in each path node, assess emission intensity and process activity, determine the difference in the impact of process path on carbon footprint, calculate the path carbon offset difference value, and obtain the path impact index value. S113: Call the path influence index value, filter and compare the carbon offset degree of each path, filter the process path compression objects, and perform structural adjustment and hierarchical reconstruction of the process nesting structure relationship, establish the mapping relationship between the path set number and the compression structure, and generate the path number sequence.

4. The carbon footprint accounting method considering the entire life cycle according to claim 3, characterized in that, The specific steps for obtaining the path reconstruction connection number set are as follows: S211: Based on the path numbering sequence, collect the node number in each path, detect the number of emission inputs and emission outputs corresponding to the node, normalize and subtract them, and combine them with the node energy consumption source type data to generate the node carbon transfer deviation value. S212: Call the node carbon transfer deviation value, extract the emission input and output, energy consumption source ratio and emission ratio between node pairs, calculate the carbon transfer efficiency between nodes, calculate the carbon transfer efficiency difference index value of node pairs, identify the node number with abnormal transfer efficiency, and establish a set of abnormal carbon transfer node numbers. S213: Call the set of abnormal carbon transfer node numbers, remove the path corresponding to the abnormal node number from the process network, and re-establish the sequential connection of the remaining nodes after removal. Based on the node connection relationship of the adjusted path, establish a path reconstruction connection number set.

5. The carbon footprint accounting method considering the entire life cycle according to claim 4, characterized in that, The specific steps for obtaining the carbon factor fit set are as follows: S311: Reconstruct the connection number set according to the path, detect the load change rate and unit emission quantity of each running node in the path network, calculate the trend curve of the two data, identify the intersection of the trend curves, extract the path segment number corresponding to the intersection, and generate a set of turning segment numbers. S312: Call the set of transition section numbers, extract the load control type, emission item combination and energy consumption structure distribution in the transition section, normalize each feature data in the section, and generate a set of transition section feature values. S313: Based on the feature value set of the transition segment, a similarity value set is formed by matching it with the corresponding condition fields in the carbon factor library, the carbon emission factor of the current transition segment is determined, and a carbon factor fitting set is established.

6. The carbon footprint accounting method considering the entire life cycle according to claim 5, characterized in that, The specific steps for obtaining the carbon footprint verification information are as follows: S411: Call the carbon factor adaptation set, collect the energy input types and energy output composition of the path segments according to the path segment order in the connection number set, determine the difference combination type and transmission characteristics of input and output between path segments, perform structural marking on the conversion relationship, and establish an energy conversion segment number list. S412: Call the energy conversion segment number list, identify the energy consumption distribution type and heat loss conversion ratio characteristics of each segment in the list, assess the concentration of heat loss phenomenon during the transfer process, and determine the inversion critical position based on the heat loss conversion degree to establish a heat loss inversion critical position set; S413: Based on the set of critical positions for heat loss inversion, accumulate the energy input data before the critical position and compare it with the recorded emission monitoring data to generate carbon footprint accounting verification information.

7. The carbon footprint accounting method considering the entire life cycle according to claim 6, characterized in that, The process of determining the critical position of inversion based on the degree of heat loss conversion is as follows: obtain the heat loss conversion ratio characteristic value of each segment in the energy conversion segment number list, arrange all heat loss conversion ratio characteristic values ​​in the path segment order, and use the rate of change of the difference in heat loss conversion ratio between adjacent path segments as the judgment basis to identify the path segment interval where the heat loss conversion ratio increases continuously and exceeds the judgment benchmark. The judgment benchmark is the critical judgment threshold for heat loss inversion calculated based on the weighted average rate of change of the heat loss conversion ratio of the entire path segment. The process of obtaining the critical threshold for heat loss inversion is as follows: the heat loss conversion ratio characteristic value of each segment in the energy conversion segment number list is numerically weighted with the unit energy consumption value of its corresponding path segment, and the weighted result is compared with the average heat loss. The node position with the largest offset value and the rate of change of change is extracted as the reference point for the sudden change of heat loss trend, and the rate of change of the heat loss conversion ratio of the reference point is used as the critical threshold for heat loss inversion.

8. The carbon footprint accounting method considering the entire life cycle according to claim 1, characterized in that, The method further includes: S5: Based on the carbon footprint accounting verification information, analyze the carbon factor level and unit type of each path node, evaluate the matching relationship between emissions and functional units, convert carbon factors based on the unit conversion ratio, collect the conversion results, summarize carbon values ​​by level, and generate multi-level carbon total data. The multi-layered total carbon data includes converted path carbon emission values, structural hierarchy collection codes, and functional unit affiliation relationships.

9. The carbon footprint accounting method considering the entire life cycle according to claim 8, characterized in that, The specific steps for obtaining the total carbon aggregation data at multiple levels are as follows: S511: Based on the carbon footprint accounting verification information, detect the carbon factor level type and unit type corresponding to each path node, calculate the matching value between node emissions and functional units, pair and map the emissions and functional unit information of the level nodes, and generate level node mapping data. S512: Call the hierarchical node mapping data, convert the carbon factor across levels based on the unit conversion ratio, calculate the carbon factor conversion value corresponding to each path segment, and obtain the path segment conversion result set; S513: Based on the path segment conversion result set, summarize the carbon value of each path segment according to the structural hierarchy, calculate the total carbon collection within the hierarchical structure, collect and summarize the data and classify and number it according to the hierarchy to generate multi-level carbon collection total data.

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