Coal gangue full-process-chain carbon footprint accounting method and accounting device

Abstract

This invention discloses a method and apparatus for calculating the carbon footprint of the entire coal gangue production chain, belonging to the field of carbon accounting technology for solid waste resource utilization. This invention establishes the accounting boundaries for the entire coal gangue resource utilization process, constructs a database of differentiated emission factors adapted to different operating conditions, calculates carbon emissions item by item based on measured and verified data from the entire process, establishes a two-dimensional carbon sink deduction system and standardizes the carbon sink allocation rules for co-produced products, and introduces an error propagation model to correct the accounting data. This invention overcomes the shortcomings of traditional accounting methods, such as incomplete process boundaries, weak specificity of emission factors, and inability to adapt to differentiated production conditions. It solves the problems of large data deviations and incomplete carbon sink accounting, effectively improving the completeness, accuracy, and standardization of carbon footprint accounting for coal gangue silicon-aluminum extraction, and achieving accurate and reliable standardized carbon footprint accounting for the entire process chain.

Description

Technical Field

[0001] This invention belongs to the field of carbon accounting technology for solid waste resource utilization, specifically involving a method and device for carbon footprint accounting of coal gangue throughout the entire process chain. It is applicable to the quantitative accounting of carbon emissions from the entire process of extracting silicon and aluminum from high-alumina coal gangue and low-alumina coal gangue through alkaline or acid leaching. Background Technology

[0002] Coal gangue is rich in silicon and aluminum, and can be used to produce high-value-added products such as alumina and silica. Its resource utilization value is extremely high. Accurate and complete carbon footprint accounting of the entire process chain is the key to evaluating the low-carbon level of its resource utilization process, determining carbon benefits, and optimizing the process to reduce emissions. At present, the process of extracting silicon and aluminum from coal gangue has problems such as high energy consumption and differentiated carbon emissions, such as high-temperature roasting and acid-base leaching. Moreover, the existing industry standards only provide framework accounting requirements, and the existing accounting system is difficult to adapt to the refined accounting needs of this process.

[0003] Existing technologies disclose a carbon footprint accounting scheme for the entire life cycle of coal-based solid waste. This scheme determines the accounting boundary by combining application scenarios, constructs process units adapted to purchased materials, related processes, and direct emissions, and establishes a carbon footprint model by integrating the allocation methods of symbiotic products, thereby achieving carbon emission accounting and error analysis for the resource utilization process of coal-based solid waste. However, this existing technology only accounts for carbon emissions from the resource utilization process and indirect emission reductions from resource utilization. It cannot quantify the direct carbon sequestration amount from the mineralization reaction of residues in the coal gangue-to-silicon-aluminum process, and cannot achieve accurate carbon sink deduction accounting combining direct and indirect carbon consumption. This results in low accuracy of the net carbon footprint accounting results for the entire coal gangue-to-silicon-aluminum process chain, failing to truly reflect the actual low-carbon level of the process. Summary of the Invention

[0004] The main objective of this invention is to provide a method and apparatus for calculating the carbon footprint of the entire coal gangue process chain, aiming to solve the problems of incomplete accounting boundaries, weak targeting of emission factors, and inability to adapt to different process conditions in the existing carbon footprint accounting of coal gangue for silicon-aluminum resource recovery.

[0005] To achieve the above objectives, this invention provides a method for calculating the carbon footprint of coal gangue across the entire process chain, the method comprising the following steps: This study defines standardized accounting boundaries for the entire process chain, covering coal gangue pretreatment, roasting activation, acid-base leaching, alumina extraction, silica preparation, and residue mineralization. It establishes a differentiated emission factor database for coal gangue resource utilization, categorized by activation atmosphere type, acid-base system type, and process temperature range. Simultaneously, it collects various measured data from the entire process chain and performs data normalization verification to obtain measured data on the standardized activity levels of each process. Based on the measured data, it matches specific emission factors and calculates the direct and indirect carbon emissions for each production stage. It constructs a dedicated carbon sink calculation module for carbon mineralization to calculate the total carbon sink deduction corresponding to direct and indirect carbon sequestration. According to the standardized allocation criteria for co-products, it allocates the total carbon sink deduction to various co-products. Finally, it introduces an error propagation analysis model, combining emission factor statistical deviations and measured data fluctuation errors, to perform error propagation calculations on the entire process chain accounting results, quantifying uncertainty and determining credible confidence intervals, and outputting the final carbon footprint data.

[0006] Optionally, the emission factor deviation is the inherent statistical deviation of factors under different operating conditions in the differentiated emission factor database, caused by experimental and statistical sample fitting; the measured data fluctuation error is the measurement deviation caused by instrument measurement, on-site operating condition fluctuation, and sampling detection. Data normalization verification only removes outliers and cannot eliminate this type of inherent fluctuation error.

[0007] Optionally, when establishing a differentiated emission factor database for the resource utilization of coal gangue, factor assignment can be completed in three ways: setting graded emission factors according to three types of roasting atmospheres: inert, oxidizing, and reducing; matching reagent consumption emission factors according to acidic and alkaline leaching systems; and correcting process energy emission factors based on low, medium, and high temperature gradients.

[0008] Optionally, the differentiated emission factor database covers the differentiated emission factors of six core process units: coal gangue pretreatment, roasting activation, acid-base leaching, alumina extraction, silica preparation, and residue mineralization treatment. Among them, pretreatment covers carbon emissions from electricity, roasting activation is adapted to 25%~35% oxygen-enriched atmosphere and air atmosphere conditions, acid-base leaching covers emission sources of electricity, reagents, and steam, alumina extraction is adapted to Bayer process and acid process, silica preparation distinguishes external flue gas, process tail gas and carbon dioxide sources, and residue mineralization treatment covers carbon emissions from electricity and reagent preparation.

[0009] Optionally, direct carbon emissions include direct carbon emissions from fuel combustion, and indirect carbon emissions include carbon emissions implied by purchased energy. Fuel combustion emissions are calculated based on fuel consumption and specific emission factors, while carbon emissions implied by purchased electricity and heat are calculated based on corresponding benchmark emission factors and actual energy consumption.

[0010] Optionally, in the process of constructing a carbon sink calculation module dedicated to carbon mineralization, the quantitative correlation between the calcium and magnesium content of the residue, mineralization conditions and carbon dioxide fixation rate is fitted through orthogonal experiments. The mineralization conditions include temperature, pressure, duration and efficiency coefficient. Based on the fitted formula, the carbon sequestration amount is calculated, and the direct carbon sequestration amount of the process and the indirect emission reduction amount of auxiliary energy consumption are distinguished to complete the carbon sink deduction accounting.

[0011] Optionally, the total carbon offset corresponding to indirect carbon sequestration includes the emission reduction from the resource substitution of mineralized residues. After modification, mineralized residues can replace natural building materials and cementitious materials. Based on the carbon emission benchmark of the substitute materials, the emission reduction generated in the mining of natural minerals and the processing of raw materials is calculated.

[0012] Optionally, the error propagation analysis model is constructed based on the weighted coupling uncertainty of each emission link, and the standardized uncertainty threshold of each core unit emission factor is predefined, specifically: fuel 5%~10%, electricity 5%~8%, process 10%~20%, mineralization efficiency 10%~25%, residue mineralization treatment 8%~12%, and pretreatment 5%~10%, which can realize the traceability of independent uncertainty of each process and sensitivity analysis.

[0013] Optionally, relying on the carbon sink calculation module and error propagation analysis model dedicated to carbon mineralization, the carbon sink accounting results and error correction results are calibrated in conjunction. Based on the total carbon emissions of the entire process chain, the net carbon emissions of the coal gangue resource utilization process are obtained by deducting the carbon consumption of direct mineralization and the emission reduction of indirect resource utilization substitution.

[0014] Optionally, the carbon emission allocation of co-existing products follows the ISO14067:2018 international standard, and is configured with three optional allocation modes: economic value allocation mode, quality allocation mode, and energy consumption allocation mode. The allocation calculation can be carried out by selecting one or combining them according to the project accounting needs.

[0015] In addition, to achieve the above objectives, the present invention also provides a carbon footprint accounting device for the entire coal gangue process chain, including an accounting boundary definition module, a differentiated emission factor database construction module, a full-process data acquisition and verification module, a sub-item carbon emission accounting module, a carbon sink deduction accounting module, a co-produced product carbon sink allocation module, and an error analysis and result output module.

[0016] The accounting boundary delineation module is used to define standardized accounting boundaries covering the entire process chain of coal gangue pretreatment, roasting activation, acid and alkali leaching, alumina extraction, silica preparation and residue mineralization.

[0017] The differentiated emission factor database module is used to establish a database of differentiated emission factors for the resource utilization of coal gangue. The emission factors are stored in categories according to activation atmosphere type, acid-base system type and process temperature range for subsequent calculation and matching.

[0018] The full-process data acquisition and verification module is used to synchronously collect energy consumption data, reagent dosage, material inbound and outbound ledgers, mineralization process operating parameters, and on-site dynamic measured data of the entire process chain, and to complete data normalization verification and output the measured data of standardized activity levels of each process.

[0019] The sub-item carbon emission accounting module is connected to the differentiated emission factor database module and the full-process data acquisition and verification module. It is used to receive standardized activity level measured data, match specific emission factors, and calculate the direct and indirect carbon emission values ​​of each production link.

[0020] The carbon sequestration deduction calculation module is equipped with a dedicated carbon sequestration calculation module for carbon mineralization. This module combines the calcium and magnesium content of solid waste, mineralization reaction conditions, and carbon dioxide fixation efficiency to calculate the direct and indirect carbon sequestration amounts, thereby obtaining the total carbon sequestration deduction amount for the entire process chain.

[0021] The carbon sequestration allocation module for co-produced products is connected to the carbon deduction calculation module. It is used to allocate the total carbon deduction to various co-produced products such as alumina, silica, and mineral residues according to the standardized allocation criteria for co-produced products.

[0022] The error analysis and results output module has a built-in error propagation analysis model, which is used to quantify the differential deviation of emission factors and the fluctuation error of measured data, define the credible confidence interval for accounting, and output the carbon footprint accounting data of the entire coal gangue process chain and each co-produced product.

[0023] The beneficial effects that this invention can achieve are: This invention proposes a method and apparatus for calculating the carbon footprint of the entire coal gangue production chain. By defining standardized accounting boundaries for the entire process from coal gangue resource recovery pretreatment to residue mineralization, constructing a database of differentiated emission factors adapted to different operating conditions, and calculating carbon emissions item by item based on measured and verified data from the entire process, a dual-dimensional carbon sink offsetting system (direct and indirect) is established, and carbon sink allocation for co-produced products is based on international standards and specifications. Simultaneously, an error propagation model with threshold limitations is used to complete data correction. This addresses the problems of incomplete accounting boundaries, weak specificity of emission factors, inability to adapt to differentiated process conditions, and low reliability of calculation results in existing carbon footprint calculations for coal gangue silicon-aluminum resource recovery. It achieves accurate, reliable, and standardized carbon footprint calculation for the entire coal gangue silicon-aluminum resource recovery process.

[0024] This invention, by defining a standardized accounting boundary covering the entire process from pretreatment, roasting activation, acid-base leaching, alumina extraction, silica preparation to residue mineralization, completely solves the problem of traditional carbon footprint accounting only capturing a portion of the process and resulting in incomplete accounting scope and distorted accounting results. It achieves full coverage accounting of carbon emissions and carbon sinks throughout the entire process of coal gangue resource utilization, ensuring the integrity and comprehensiveness of the accounting results.

[0025] This invention abandons traditional general-purpose emission factors and establishes a differentiated emission factor database based on activation atmosphere type, acid-base system, and temperature gradient classification. It is fully compatible with six core process units, including pretreatment, roasting activation, acid-base leaching, alumina extraction, silica preparation, and residue mineralization treatment, as well as various actual production conditions. It can accurately match specific emission parameters according to on-site production conditions, effectively solving the problems of general-purpose emission factors being unable to adapt to differentiated production scenarios and having low calculation accuracy, and significantly improving the pertinence and accuracy of carbon emission accounting for each process.

[0026] This invention adopts a multi-dimensional measured data collection and normalization verification mode across the entire process chain. It accurately collects measured data on energy consumption, reagents, materials, and process operation throughout the entire process and completes standardized verification. Combined with dedicated emission factors, it calculates direct carbon emissions from fuel combustion and indirect carbon emissions from purchased energy, distinguishing multiple carbon emission sources. This ensures that the calculation process fully reflects actual production conditions, avoids numerical deviations caused by traditional theoretical estimations, and effectively guarantees the authenticity and reliability of the basic data for calculation.

[0027] This invention constructs a carbon sink calculation module specifically for carbon mineralization. It fits the quantitative correlation between the calcium and magnesium content of the residue, mineralization conditions, and carbon dioxide fixation rate through orthogonal experiments. At the same time, it covers a two-dimensional carbon sink accounting that includes direct carbon fixation in the process and indirect carbon fixation through resource-based substitution for emission reduction of mineralized residue. This solves the shortcomings of traditional carbon sink accounting that only counts a single carbon fixation dimension, has incomplete carbon sink deduction accounting, and has low values. It accurately restores the true carbon emission reduction capacity of coal gangue resource utilization process.

[0028] This invention is strictly based on the ISO14067:2018 international standard and configures three optional carbon sink and carbon emission allocation modes for cogeneration products: economic value, quality, and energy consumption. It can be flexibly adapted and selected according to the accounting needs of different projects, solving the problems of no unified standard, unreasonable allocation results, and insufficient fairness in the traditional allocation of carbon emissions and carbon sinks for cogeneration products, and ensuring the standardization and fairness of multi-product collaborative accounting.

[0029] This invention introduces an error propagation analysis model with precise threshold limits. It sets exclusive uncertainty thresholds for each process unit, which can quantify the error deviation of each process, realize uncertainty source tracing and sensitivity analysis, define the credible confidence interval of the accounting results, and simultaneously link the carbon sink accounting results to complete data calibration. It accurately deducts the two-dimensional carbon sink offset amount to obtain the net carbon emissions, which solves the pain points of traditional accounting that cannot quantify errors, cannot determine the credibility of the results, and has no traceability, and greatly improves the accuracy and credibility of carbon footprint accounting results. Attached Figure Description

[0030] Figure 1 This is a flowchart of the method of the present invention; Figure 2 This is a schematic diagram of the method flow of the present invention; Figure 3 This is a schematic diagram comparing the carbon footprint distribution results of alumina, silica, and mineralized residue in this invention. Figure 4 This is a schematic diagram of the uncertainty propagation model of the present invention. Detailed Implementation

[0031] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present invention.

[0032] Existing technologies for carbon footprint accounting in the coal gangue-to-silicon-aluminum resource recovery process can only statistically analyze carbon emissions generated during the resource recovery process and indirect emission reductions. They cannot quantify the direct carbon sequestration generated by the mineralization reaction of residues within the coal gangue-to-silicon-aluminum system. This makes it difficult to establish a precise two-dimensional carbon offset accounting mechanism that couples direct and indirect carbon offsets, resulting in insufficient accuracy in the net carbon footprint accounting results for the entire coal gangue-to-silicon-aluminum process chain, and failing to objectively characterize the true low-carbon performance of the process. To address these shortcomings, this invention aims to provide a method and apparatus for carbon footprint accounting across the entire coal gangue process chain, effectively solving the technical problems of insufficient accuracy, single dimension, and distorted results in existing accounting methods, and achieving accurate carbon footprint accounting for the entire coal gangue-to-silicon-aluminum process.

[0033] First embodiment: refer to Figure 1 , Figure 2 As shown in the figure, this embodiment discloses a method for calculating the carbon footprint of the entire coal gangue process chain. The carbon footprint calculation method includes the following steps: Define standardized accounting boundaries, which cover the entire process chain of coal gangue pretreatment, roasting and activation, acid and alkali leaching, alumina extraction, precipitated silica preparation and residue mineralization treatment; Establish a differentiated emission factor database for the resource utilization of coal gangue, wherein the emission factors are classified according to the type of activation atmosphere, the type of acid-base system, and the process temperature range; Simultaneously collect energy consumption data, reagent dosage, material inbound and outbound ledgers, mineralization process operating parameters, and on-site dynamic measured data of the entire process chain, and complete data normalization and verification. Based on the measured data of standardized activity levels of each process in the entire process chain, the corresponding exclusive emission factors are matched, and the direct and indirect carbon emission values ​​of each production link are calculated separately. Construct a dedicated carbon sink calculation module for carbon mineralization, and calculate the total carbon sink deduction corresponding to direct and indirect carbon sequestration by combining the calcium and magnesium content of solid waste, mineralization reaction conditions and carbon dioxide fixation efficiency. Based on the standardized allocation criteria for co-produced products, the total carbon sink deduction amount calculated is allocated to various co-produced products such as alumina, silica, and mineral residues. An error propagation analysis model is introduced to quantify the differential deviation of emission factors and the fluctuation error of measured data, define the credible confidence interval for carbon footprint accounting, and output the final accounting data.

[0034] Detailed Implementation Instructions for the Technical Solution: This embodiment uses the high-alumina coal gangue oxygen-enriched roasting-alkali leaching of silica and aluminum-medium temperature mineralization process (annual production of 10,000 tons of alumina and 8,000 tons of silica) as the accounting carrier.

[0035] Step 1: Define the standardized full-process accounting boundary, strictly covering the six core process chains: coal gangue pretreatment (crushing, grinding, drying), roasting and activation (25%~35% oxygen-enriched atmosphere roasting), acid and alkali leaching (sodium hydroxide acid and alkali leaching), alumina extraction (Bayer process), silica preparation (carbon fractionation), and residue mineralization treatment (medium-temperature high-pressure CO2 mineralization and carbon fixation). At the same time, incorporate auxiliary production systems (electricity, steam supply, and reagent preparation) to completely solve the problems of fragmented traditional accounting boundaries and omissions in process calculations.

[0036] Step 2: Construct a differentiated emission factor database and strictly classify and assign values ​​according to three dimensions: distinguishing activation atmosphere by oxygen enrichment / air, distinguishing acid-base system by alkaline leaching / acid leaching, and distinguishing process temperature by low / medium / high temperature gradient. Abandon general and extensive emission factors and achieve one-to-one exclusive matching between process and emission factor.

[0037] Step 3: Data collection and normalization verification of the entire supply chain. Collected data includes: electricity, natural gas, and steam consumption data for each process; dosage of reagents such as NaOH and flocculants; inventory records of coal gangue, products, and residues; operating parameters such as mineralization temperature, CO2 partial pressure, and reaction time; and dynamic measured data of on-site equipment operation. Normalization is achieved through unit standardization, outlier removal, and parallel data mean verification to ensure the accuracy of the basic data.

[0038] Step 4: Calculate carbon emissions by stage. Based on normalized measured activity data, match the database with specific emission factors, and calculate the direct carbon emissions from fuel combustion and the indirect carbon emissions from purchased energy in each stage of pretreatment, roasting, leaching, extraction, preparation, mineralization, and residue mineralization treatment, so as to achieve full-chain, comprehensive accounting.

[0039] Step 5: Two-dimensional carbon sink deduction calculation. A dedicated carbon sink calculation module is built. Based on the active calcium and magnesium content of the residue, combined with the mineralization temperature, pressure, reaction time and measured carbon fixation efficiency, the direct carbon fixation amount of the mineralization reaction and the indirect carbon fixation amount of the residue resource substitution are calculated simultaneously, and the total carbon sink deduction value is obtained by summing them up.

[0040] Step 6: Standardized allocation of multiple products. Based on the ISO14067:2018 international standard allocation criteria, the total carbon credit and net carbon emissions are accurately allocated to three symbiotic products: alumina, silica, and mineral residues, solving the problem of unfounded allocation and chaotic results for multiple products.

[0041] Step 7: Introduce an error propagation analysis model, combine the statistical deviation of emission factors and the fluctuation error of measured data, perform error propagation calculation on the full process chain accounting results, quantify the uncertainty and determine the credible confidence interval, and output the final carbon footprint data.

[0042] The emission factor deviation is the inherent statistical bias of factors under different operating conditions in the differentiated emission factor database, resulting from experimental and statistical sample fitting. The measured data fluctuation error is the measurement deviation caused by instrument measurement, on-site operating condition fluctuations, and sampling detection. Data normalization verification only removes outliers and cannot eliminate this type of inherent fluctuation error.

[0043] This implementation case is applicable to the final stage of carbon footprint accounting for the entire life cycle of industrial products. After completing all core calculations such as carbon emission accounting for all processes, carbon sink deduction calculation, and carbon allocation for multi-product products, it conducts a full-process uncertainty error analysis. The entire process does not involve calculation formulas, focuses on practical application scenarios, and completes data credibility verification and final output.

[0044] Identify two core sources of error (inherent, non-eliminable errors): This error analysis only addresses the inherent uncertainties of the parameters themselves and does not verify human errors such as previous manual calculations or formula application. The core errors are divided into two categories: all errors are inherent fluctuations in industry statistics and on-site production and cannot be eliminated through data normalization or outlier removal. Emission factor statistical bias: The emission factors used in the calculation process for different operating conditions are all generated from a large number of industry tests and statistical sample fitting. Differences in different production conditions and test samples will cause fixed statistical biases in the emission factors of various fuels, electricity, raw materials, and processes, which are inherent errors of the database itself.

[0045] Field measurement data fluctuation error: The measured data of each process activity level (energy consumption, material consumption, output, operating parameters, etc.) are subject to normal fluctuation errors due to the influence of the accuracy of field instruments, dynamic fluctuations in production conditions, and deviations in manual sampling and testing. The preliminary data preprocessing only removes extreme abnormal data and cannot eliminate these normal inherent fluctuations.

[0046] Establish end-to-end error propagation analysis logic: Based on the error propagation analysis model, and benchmarking against the complete carbon footprint accounting chain, the error propagation patterns are traced and deduced segment by segment in the four core chains to ensure that the error analysis covers the entire process without omission: Direct carbon emission chain: Track carbon emission errors generated by direct combustion and process reactions in production processes, match corresponding process operating condition emission factor deviations and on-site energy consumption measurement fluctuation errors, and deduce the transmission impact of errors in direct carbon emission accounting.

[0047] Indirect carbon emission chain: Covering the upstream and downstream indirect emissions of purchased electricity, steam, raw materials and auxiliary materials, combining the statistical deviation of emission factors of purchased energy and materials, as well as the fluctuation of measured data of material consumption and energy consumption within enterprises, to calculate the error propagation range of indirect emissions.

[0048] Carbon offset accounting chain: For carbon offset amounts such as project greening carbon sequestration and process carbon capture, the uncertainty error of the carbon offset link is analyzed by combining the statistical factor deviation corresponding to carbon offset accounting and the fluctuation of on-site carbon offset monitoring data.

[0049] Co-production product allocation chain: For carbon emissions and carbon sink allocation results in multi-product co-production scenarios, combined with the basic factors used in the allocation calculation and the inherent errors of the measured production data, the impact of error transmission in the allocation process is deduced.

[0050] Quantifying uncertainty and defining 95% confidence intervals (practical application): Error data collection: Collect basic error parameters from all accounting processes, including the statistical deviation range marked in the emission factor database for each process and the normal fluctuation range of measured data for each batch, as the sole input for the error model.

[0051] Full-process error extrapolation: Following the calculation logic of the four major accounting links, the input errors of each link are passed down step by step, and the uncertainties of each accounting process are superimposed to finally obtain the overall error fluctuation range of the total carbon footprint of the product, thus completing the quantification of uncertainty in the entire process.

[0052] Defining a credible confidence interval: Based on the results of the summation of errors across the entire chain, and using industry-standard uncertainty evaluation criteria, a 95% confidence interval is calculated to clarify the credible fluctuation range of the final carbon footprint accounting results and define the effective credible interval of the data.

[0053] Output the final carbon footprint results (closed-loop traceability): This step is placed after all accounting and allocation work is completed and before the final data output, forming a complete accounting logic loop. The final output is no longer a single fixed value, but traceable carbon footprint data that includes core accounting values, 95% confidence intervals, explanations of error sources, and uncertainty assessment conclusions. It not only clarifies the product standard carbon footprint value, but also indicates the reasonable fluctuation range of the data, ensuring that the accounting results are scientific, reliable, and compliant with industry verification standards.

[0054] This scheme delineates the closed-loop accounting boundaries for the entire process of extracting silicon and aluminum from coal gangue, eliminating any omissions in carbon emission calculations. It employs process-specific differentiated emission factors, combined with normalized verification of measured data to solidify the data foundation. It stratifies and distinguishes between direct and indirect carbon emissions to identify high-carbon processes. It simultaneously calculates two types of carbon sinks: mineralization carbon sequestration and alternative emission reduction. It allocates the carbon footprint of multi-product combined products according to standards, adapts to carbon certification and carbon trading, and quantifies uncertainty through an error model, overcoming the shortcomings of traditional accounting methods such as fragmentation, low accuracy, underestimation of carbon sinks, and difficulty in tracing the results.

[0055] As a preferred approach, when establishing a differentiated emission factor database for the resource utilization of coal gangue, the assignment methods include: setting graded emission factors according to three types of roasting atmospheres: inert, oxidizing, and reducing; matching reagent consumption emission factors according to acidic and alkaline leaching systems; and correcting process energy emission factors based on low, medium, and high temperature gradients.

[0056] In this embodiment, the assignment logic of the emission factor database is optimized to adapt to two mainstream coal gangue silicon-aluminum extraction processes (high-alumina oxygen-enriched oxidation roasting and low-alumina air inert roasting + acid leaching process), and the graded assignment rules are implemented: 1. Calcination Atmosphere Classification and Assignment: Three operating conditions are distinguished: inert (conventional low-temperature air calcination), oxidation (25%~35% oxygen-enriched calcination), and reduction (calcination with added strong reducing agents), with gradient emission factors set for each. The power emission factor for oxidation-enriched calcination is within the normal range, while the power emission factor for conventional air-inert calcination is slightly higher than that for oxygen-enriched calcination. The reduction atmosphere has a dedicated emission factor due to agent consumption, enabling differentiated accounting for different atmosphere processes.

[0057] 2. Precise matching of acid-base systems: For alkaline leaching systems, specific emission factors are matched for NaOH preparation, alkaline solution heating, stirring and filtration; for acidic leaching systems, specific emission factors are matched for sulfuric acid / hydrochloric acid preparation, acid regeneration and acid treatment, completely distinguishing the differences in reagent carbon emissions between the two core leaching processes.

[0058] 3. Temperature gradient factor correction: The process is divided into three zones: low temperature, medium temperature, and high temperature. The emission factors for steam, electricity, and fuel energy are corrected according to the gradient. High-temperature roasting and high-temperature leaching processes have higher energy consumption and losses, so the emission factors are set to the upper limit. Low-temperature processes are set to the lower limit to match the actual energy consumption characteristics of the processes.

[0059] For the process of extracting silicon and aluminum from coal gangue, roasting emission parameters are assigned according to the oxidizing, inert, and reducing atmospheres. Dedicated accounting factors are matched for different acid and alkali leaching routes, and temperature gradients are introduced to correct the emission factors. This fully takes into account the emission differences caused by roasting atmosphere, leaching system and production temperature, and effectively solves the accuracy defects of traditional accounting methods, such as insufficient differentiation of working conditions, general calculation and neglect of temperature influence.

[0060] Furthermore, the differentiated emission factor database covers the differentiated emission factors of six core process units: pretreatment, roasting and activation, acid and alkali leaching, alumina extraction, silica preparation, and residue mineralization. The pretreatment covers carbon emissions from electricity, and the roasting and activation is adapted to 25%~35% oxygen-enriched atmosphere and air atmosphere conditions. The acid and alkali leaching covers sources of electricity, reagents, and steam emissions. The alumina extraction is adapted to the Bayer process and acid process. The silica preparation distinguishes between external flue gas and process tail gas carbon dioxide sources. The residue mineralization covers carbon emissions from electricity and reagent preparation.

[0061] This embodiment, based on hierarchical value assignment, improves the database to cover all scenarios and accurately adapts to all mainstream process units and emission sources in the industry, corresponding to the two core implementation scenarios of this invention (alkaline oxygen-enriched process and acid air process): 1. Preprocessing unit: Covers the power consumption of the preprocessing system.

[0062] 2. Calcination and activation unit: It is specially adapted to two mainstream industrial calcination conditions: 25%~35% oxygen-enriched oxidizing atmosphere and conventional air inert atmosphere. It is configured with corresponding power and fuel emission factors to cover the activation production needs of high-activity and conventional coal gangue.

[0063] 3. Acid-base leaching unit: Comprehensively covers the three core emission sources, including the power consumption for stirring, conveying and filtering, the consumption for NaOH reagent preparation, and the consumption for process heating steam, and calculates all carbon emission sources of the alkali leaching process without omission.

[0064] 4. Alumina Extraction Unit: Bidirectionally adaptable to mainstream industrial processes such as the Bayer process (high temperature and high pressure alkaline process) and the acid process (hydrochloric acid / sulfuric acid pressure leaching), each configured with dedicated process emission factors to adapt to aluminum extraction routes for coal gangue raw materials with different alumina levels.

[0065] 5. Silica Preparation Unit: Innovatively distinguishes between CO2 sources and configures differentiated factors for two production modes: carbon content from external industrial flue gas and carbon content from process-generated tail gas, thus solving the problem of carbon emission accounting deviation when preparing silica from different carbon sources.

[0066] 6. Residue mineralization treatment unit: Fully covers the electricity consumption of wastewater and waste gas treatment, carbon emissions of flocculant / neutralizing agent preparation, and fills the accounting gaps in the end-of-pipe treatment process.

[0067] This solution achieves full coverage of six core process units, adapts to mainstream process routes such as acid-base and oxygen-enriched / air-based processes, and improves the universality of accounting. It comprehensively analyzes all emission sources of each unit, and coordinates the carbon emissions of electricity, heat, reagents, and raw materials to avoid omissions in single-point processes. At the same time, it distinguishes the emission characteristics of different carbon dioxide gas sources in the preparation of precipitated silica, and matches low-carbon tail gas and conventional flue gas carbon separation processes, filling the accounting gaps in subdivided fields and improving the shortcomings of traditional accounting scenarios such as insufficient adaptability, missing emission sources, and distortion of precipitated silica process calculations.

[0068] As a preferred option, direct carbon emissions include direct carbon emissions from fuel combustion, while indirect carbon emissions include carbon emissions implied by purchased energy. Fuel combustion emissions are calculated based on fuel consumption and specific emission factors, while carbon emissions implied by purchased electricity and heat are calculated based on corresponding benchmark emission factors and actual energy consumption.

[0069] This embodiment clarifies the stratified carbon emission accounting system, and the calculation rules are as follows: 1. Direct Carbon Emission Accounting: This method only tracks carbon emissions from fuel combustion at the process site, primarily from the combustion of fossil fuels such as natural gas and coal. Based on the actual consumption of various fuels and their corresponding specific emission factors, the direct carbon emissions from on-site fuel combustion are accurately calculated. Combined with the actual production conditions of the project, the total direct carbon emissions corresponding to the consumption of fuels such as natural gas at each production stage can be accurately calculated.

[0070] 2. Indirect Carbon Emission Accounting: This involves calculating the carbon emissions inherent in purchased energy within the plant area, including purchased electricity and steam. The electricity emission factor uses the latest benchmark value announced by the Ministry of Ecology and Environment, while the steam emission factor is determined according to national standards. Based on the actual purchased electricity and steam energy consumption data for each process, the indirect carbon emissions generated by purchased energy throughout the entire process are calculated.

[0071] This scheme clearly distinguishes between direct fuel combustion emissions and indirect emissions from purchased energy sources. The classification rules are in line with IPCC and domestic carbon accounting standards, and the system is standardized and traceable. It is equipped with standardized accounting rules and authoritative benchmark factors, abandons empirical estimation methods, and achieves reproducible calculation results and comparability between different projects, solving the problems of confused accounting boundaries and inconsistent calculation methods.

[0072] As a preferred approach, in constructing the dedicated carbon sink calculation module for carbon mineralization, an orthogonal experiment is used to fit the quantitative correlation between the calcium and magnesium content of the residue, mineralization conditions, and carbon dioxide fixation rate. The mineralization conditions include temperature, pressure, duration, and liquid-to-solid ratio. Based on the fitted pattern, the carbon sequestration amount is calculated, distinguishing between the direct carbon sequestration amount from the process and the indirect emission reduction amount from auxiliary energy consumption, thus completing the carbon sink deduction accounting.

[0073] This embodiment establishes a precise and quantitative carbon sequestration accounting model, calibrates the correlation between core parameters through orthogonal experiments, and implements a two-dimensional carbon sequestration calculation: 1. Quantitative fitting of parameters: Taking the content of active CaO and MgO in the residue as the core variables, and the mineralization temperature, CO2 partial pressure, reaction time and efficiency coefficient as operating condition variables, a four-factor three-level orthogonal experiment was conducted to accurately fit the quantitative correlation between carbon fixation rate and raw material characteristics and process conditions, and to quantify the impact of raw material calcium and magnesium content on carbon fixation potential.

[0074] 2. Calibration of Reaction Efficiency Coefficient: High-pressure experiments using a thermogravimetric analyzer were conducted to calibrate the carbon fixation efficiency coefficient under different temperature, pressure, and reaction duration conditions. This clarified the efficiency range corresponding to different mineralization conditions, providing a standardized basis for calculating carbon fixation under different process conditions. The mineralization reaction efficiency is higher under medium-temperature and high-pressure conditions, while the carbon fixation efficiency is relatively lower under normal temperature and pressure conditions, perfectly reflecting the characteristics of actual mineralization production.

[0075] 3. Multidimensional Carbon Sequestration Calculation: The theoretical carbon sequestration amount is calculated based on the fitted carbon sequestration law, and the actual direct carbon sequestration amount is obtained by correcting it with the measured efficiency coefficient under actual operating conditions. At the same time, the indirect emission reduction brought about by the optimization of auxiliary process operation is calculated simultaneously, realizing the accurate quantification of carbon sequestration deduction in two dimensions. The carbon sequestration potential of coal gangue residue of different qualities varies significantly, and can be accurately distinguished and calculated by combining raw material characteristics and production conditions.

[0076] This scheme relies on orthogonal experimental fitting of parameters to quantitatively correlate them, abandoning empirical estimation, so that the calculation of carbon sequestration has experimental support; it covers the efficiency coefficient of all working conditions of temperature, pressure and time, and is suitable for various mineralization processes; at the same time, it distinguishes between two types of carbon sinks, namely direct carbon sequestration and indirect emission reduction, fully reflecting the low-carbon benefits of mineralization processes, and solving the problems of empirical carbon sink accounting, lack of unified parameter standards and single statistical dimensions.

[0077] Furthermore, the total carbon offset corresponding to indirect carbon sequestration includes the emission reduction from the resource substitution of mineralized residues; the mineralized residues are modified to replace natural building materials and cementitious materials, and the emission reductions generated in the mining of natural minerals and processing of raw materials are calculated based on the carbon emission benchmark of the substitute materials.

[0078] This embodiment accurately quantifies the benefits of indirect carbon sequestration and emission reduction, and implements the carbon sequestration accounting rules for residue resource utilization as a substitute: After modification, mineralized coal gangue residue can directly replace natural resources such as sand and gravel, cementitious materials, and limestone roadbed fillers, reducing carbon emissions from the mining, crushing, calcination, and processing of natural minerals. Based on the amount of residue utilized, the type of substitute materials, and the corresponding carbon emission benchmarks, the indirect carbon emission reductions resulting from the residue replacing natural raw materials can be accurately calculated and fully included in the total carbon offset range. The resource utilization rate of residue and the types of building materials substituted vary among different projects; therefore, the corresponding indirect emission reductions can be accurately calculated based on actual operating conditions.

[0079] This plan adds a new dimension of carbon sequestration through resource utilization, breaking through the limitations of only accounting for carbon sequestration. It quantifies the emission reduction benefits generated by the resource utilization of solid waste to replace natural raw materials, fully reflecting the low-carbon value of the entire coal gangue resource utilization chain. Furthermore, it conducts accounting based on national standard factors and solid waste resource utilization guidelines to ensure that the emission reduction results are authoritative and verifiable, supporting enterprises' carbon emission reduction statistics and low-carbon product declarations, and addressing the shortcomings of underestimating the value of carbon sequestration and lacking accounting basis for emission reduction substitution.

[0080] As a preferred approach, the error propagation analysis model is constructed based on the weighted coupling uncertainty of each emission stage. The model predefines the standardized uncertainty thresholds of emission factors for each core unit, wherein: fuel, electricity, process, mineralization efficiency, residue mineralization treatment, and pretreatment are all set with graded standardized uncertainty ranges. The error propagation analysis model can realize the source tracing and sensitivity analysis of independent uncertainties of each process.

[0081] This embodiment establishes a standardized uncertainty quantification system and achieves accurate error analysis based on a weighted coupled error propagation model: 1. Standardized uncertainty threshold assignment: Strictly set graded error ranges for each production process according to process characteristics, optimize the accurate value by combining a large number of engineering examples, match the actual production fluctuation characteristics of each process, and avoid the accounting deviation caused by uniform error value.

[0082] 2. Weighted Coupling Error Calculation: Based on the weight of each process's emissions to the total emissions, combined with the standardized uncertainty of each link, the overall accounting uncertainty is calculated through the core logic of error propagation. At the same time, it can realize independent error tracing of single processes, accurately locate the highly sensitive processes that have the greatest impact on the overall accounting accuracy, and provide a clear direction for subsequent optimization of data collection and improvement of accounting accuracy.

[0083] This solution sets graded uncertainty standardized error thresholds for each process unit to match the production fluctuation characteristics of each process; it uses a weighted coupling method to estimate errors differently to avoid error averaging; and it combines source tracing and sensitivity analysis to clarify the error contribution of each process, accurately locate highly sensitive processes, point the way for accuracy optimization, and solve the problems of lack of standards for error quantification, crude estimation methods, and difficulty in tracing errors.

[0084] As a preferred approach, relying on the carbon sink calculation module and error propagation analysis model dedicated to carbon mineralization, the carbon sink accounting results and error correction results are calibrated in a linked manner. Based on the total carbon emissions obtained from the full process chain accounting, the amount of carbon consumed by direct mineralization and the amount of emission reduction by indirect resource utilization substitution are deducted to finally obtain the net carbon emissions of the coal gangue resource utilization process.

[0085] This embodiment achieves linked calibration of carbon sink and error, completing accurate net carbon emission calculation: 1. Linked calibration mechanism: The numerical error of carbon sink accounting and the carbon emission error of each process are coupled and corrected to correct the error deviation of a single module, suppress the accumulation of errors caused by multi-step accounting, and ensure the consistency and accuracy of the overall accounting results.

[0086] 2. Net Carbon Emission Calculation: Based on the total carbon emissions calculated across the entire process chain, the direct carbon sequestration from the mineralization reaction and the indirect emission reductions from residue resource utilization are deducted sequentially to obtain the project's final net carbon emissions, forming a standardized and unified net emission calculation logic. This logic can be used to accurately calculate the net carbon emissions of coal gangue resource utilization projects with different process scales and raw material types.

[0087] 3. Error Correction Output: The overall result is calibrated by combining the uncertainty of each process, and the net carbon footprint data with a credible confidence interval is output, so that the accounting results are not only accurate, but also traceable and verifiable.

[0088] This solution relies on the carbon sink module and error model for dual-module linkage calibration to suppress the accumulation of errors caused by multi-step accounting; it adopts the unified logic of total emissions deduction for carbon sink to carry out standardized net emissions accounting, which effectively improves the problems of accumulated accounting deviations and non-standard output of results. The results can be directly used for low-carbon assessment, carbon ledger declaration and product carbon label certification.

[0089] As a preferred option, the carbon emission allocation of co-existing products follows the ISO14067:2018 international standard, and is configured with three optional allocation modes: economic value allocation mode, quality allocation mode, and energy consumption allocation mode. The allocation calculation is carried out by selecting one or combining them according to the project accounting needs.

[0090] This embodiment implements a standardized multi-product cost-sharing mechanism, adaptable to different accounting scenarios: 1. Quality-based allocation model: Applicable to scenarios where the economic value of various products is similar, net carbon emissions are allocated based on the quality of product output.

[0091] 2. Economic value allocation model (recommended): Applicable to mainstream scenarios with large differences in product value. It allocates value based on the total annual market output value, which is in line with the actual operation logic of industry and is suitable for most coal gangue multi-generation resource utilization projects.

[0092] 3. Energy consumption allocation mode: suitable for scenarios with significant differences in process energy consumption, the energy consumption of each product production process is allocated by weight.

[0093] All three modes strictly adhere to the ISO14067:2018 international standard and can be used individually or in combination with weighted averages to meet the needs of various scenarios such as scientific research accounting, enterprise application, and international certification.

[0094] This solution offers three flexible allocation modes, breaking the limitations of single quality allocation and adapting to diverse accounting scenarios. The allocation rules are aligned with the ISO14067 international carbon footprint standard, ensuring international recognition of the accounting results. This supports low-carbon certification and international carbon trading for export products, resolving the issues of rigid product allocation methods and difficulties in obtaining international recognition of the results.

[0095] refer to Figures 3-4 As shown, the method steps of the present invention will be further described in detail below with reference to embodiments: Step 1: Determine the accounting boundaries: The accounting boundary is defined to cover the entire process chain of silicon-aluminum extraction from coal gangue, including: coal gangue pretreatment unit (crushing, grinding, drying), roasting and activation unit (oxygen-enriched roasting or air roasting), acid and alkali leaching unit (sodium hydroxide solution leaching), alumina extraction unit (Bayer process or acid process), product preparation unit (carbon fraction of white carbon, alumina calcination), residue mineralization treatment unit (CO2 mineralization reaction), and residue mineralization treatment unit (wastewater treatment, waste gas treatment, waste residue dewatering and transfer).

[0096] Referring to the framework requirements of T / CECA-G0334-2024 for carbon emission accounting in the comprehensive utilization of coal gangue, the accounting boundary should cover all processes from raw material input to product output, including the main production system, auxiliary production system and ancillary production system.

[0097] The accounting boundary includes direct emissions (emissions from fossil fuel combustion and process reaction) and indirect emissions (emissions implied by purchased electricity and heat). Carbon sink deductions (mineralized carbon sequestration) are included in the accounting results for correction.

[0098] Step 2: Establish a database of emission factors specific to the silicon-aluminum extraction process: For each process step in the silicon-aluminum extraction process, a dedicated emission factor database has been established. The classification system for emission factors in each step is as follows: Process Emission factor classification Default value range Basis for determination Preprocessing Crushing, grinding, and drying (electric power) 0.57~0.68 tCO2 / MWh National power grid average emission factor combined with equipment efficiency Calcination and Activation <![CDATA[Roasting in oxygen-enriched atmosphere (O₂ 25%~35%)]]> Electricity: 0.57~0.65 tCO2 / MWh National power grid average emission factor combined with process correction air atmosphere roasting Electricity: 0.58~0.68 tCO2 / MWh 5%~10% higher than in an oxygen-rich atmosphere Acid-base leaching Electricity (mixing, conveying, filtering) 0.57~0.65tCO2 / MWh National power grid average emission factor NaOH solution preparation and discharge 1.5~2.5tCO2 / tNaOH Industry average data Heating steam discharge 0.10~0.15tCO2 / GJ GB / T32151 series standards Alumina Extraction Bayer process (high temperature and high pressure) 1.0~1.8tCO2 / tAl2O3 Industry experience data Acid method (hydrochloric acid / sulfuric acid) 1.2~2.2tCO2 / tAl2O3 Acid regeneration process included Preparation of silica Carbon fractionation 0.8~1.5tCO2 / t product <![CDATA[The source of CO₂ for carbonation has a significant impact]]> Residue mineralization treatment Wastewater treatment and exhaust gas treatment (electricity + chemicals) Electricity: 0.57~0.65 tCO2 / MWh; Chemicals: 1.0~2.0 tCO2 / t Electricity emission factor + reagent preparation factor The emission factor database distinguishes between roasting activation atmosphere type (oxygen-enriched / air), acid-base system type (alkali leaching / acid leaching), and process temperature range (low temperature <150℃, medium temperature 150~300℃, high temperature >300℃), and differentiates CO2 from different sources (fossil source / biological source).

[0099] The emission factor for electricity was taken from the latest national average emission factor for electricity released by the Ministry of Ecology and Environment. According to Announcement No. 47 of 2025 issued by the Ministry of Ecology and Environment, the national average emission factor for electricity in 2023 was 0.5306 tCO2 / MWh. The emission factor for fuel combustion was calculated as the product of carbon content per unit calorific value and oxidation rate. The carbon content per unit calorific value of diesel fuel was 2.02 × 10⁻³ tC / GJ, and the oxidation rate was taken as 98%.

[0100] Step 3: Collect activity data: Collect activity data for each process stage, including but not limited to: Energy consumption data: electricity consumption (kWh), coal / natural gas and other fuel consumption (t or m³), ​​steam consumption (GJ). Material consumption data: Sodium hydroxide consumption (t), acid reagent consumption (t), activating agent consumption (t), flocculant consumption (t), lime consumption (t). Material input and output data: coal gangue input (t), alumina output (t), silica output (t), residue output (t). Mineralization process parameters: mineralization reaction temperature (°C), CO2 partial pressure (MPa), reaction time (h), and calcium and magnesium content of residue (%).

[0101] Step 4: Calculate emissions at each stage: Based on emission factors and activity data, emissions at each stage are calculated using the following formula: Emissions from fossil fuel combustion: E 燃料 = in, AD i This represents the activity data (consumption) for the i-th type of fuel. EF i This is the CO2 emission factor for this fuel.

[0102] Hidden emissions from purchased electricity and heat: E 电力 =AD 电力 ×EF 电网 E 热力 =AD 热力 ×EF 热力 Process reaction emissions: E 过程= This mainly includes: emissions from carbonate decomposition (such as sodium carbonate decomposition in activating agents) and emissions from electrode consumption (if any).

[0103] Step 5: Set up the mineralized carbon sink accounting submodule; A mineralized carbon sequestration accounting submodule is set up to calculate the carbon sequestration deduction based on the quantitative relationship between the calcium and magnesium content of the residue, the mineralization reaction conditions and the CO2 fixation rate.

[0104] Calculation of mineralized CO2 fixation: The amount of CO2 fixed by mineralization includes two parts: direct carbon consumption and indirect carbon consumption. Direct carbon consumption refers to the amount of CO2 fixed by the active CaO and MgO components in the residue obtained after extracting silicon and aluminum from coal gangue, which undergo carbonation reaction with CO2 in the mineralization reactor to form stable carbonate minerals (CaCO3, MgCO3), i.e., the actual mass of CO2 fixed by the mineralization reaction.

[0105] The amount of direct carbon consumed (CO2 fixed by mineralization reaction) is: C 直接 =M 残渣 ×R 固碳 ×η in: M 残渣 The mass (t) of the residue that participated in the mineralization reaction; R 固碳 The theoretical CO2 fixation rate per unit mass of residue is calculated based on the content of active CaO and MgO in the residue: R 固碳 = × w CaO + × w MgO in, w CaO 、w MgO The percentages (%) of active CaO and MgO in the residue are respectively. η is the efficiency coefficient of the mineralization reaction, which is determined based on the mineralization reaction conditions: η = f ( T , P CO2 , t ) According to literature reports and experimental calibration, 1 ton of mineralized material can fix 50~300kg of CO2. Typical values ​​for the mineralization reaction efficiency coefficient are as follows: Temperature range CO2 partial pressure range reaction time Efficiency coefficient η range Normal temperature (25~35℃) 0.5~1.0MPa 4~8h 0.30~0.55 Medium temperature (120~200℃) 0.5~1.5MPa 2~4h 0.55~0.80 Medium and high temperature (200~280℃) 1.0~2.5MPa 1~3h 0.70~0.90 The value of the above-mentioned mineralization reaction efficiency coefficient η was determined based on the following experimental calibration method: Thermogravimetric analysis (TGA) or a high-pressure reactor was used to determine the mass change of the residue sample before and after the carbonation reaction under controlled conditions of temperature (±1℃), CO2 partial pressure (±0.05MPa), and reaction time. The theoretical maximum CO2 absorption was calculated based on the content of active CaO and MgO in the residue. The actual CO2 absorption was obtained through thermogravimetric analysis. η = actual CO2 absorption / theoretical maximum CO2 absorption. At least three parallel experiments were conducted for each set of experimental conditions, and the arithmetic mean was taken. The standard deviation of each data point was controlled within ±0.05.

[0106] Indirect carbon absorption refers to the carbon emissions avoided by reducing the mining and processing of natural materials through the substitution of mineralized residues for natural building materials or partial substitution of cement and other cementing materials. The substitution of mineralized residues for natural building materials includes, but is not limited to: replacing natural sand and gravel as aggregates, replacing a portion of cement as cementing materials, or replacing limestone as roadbed filler. The substitution ratio is determined according to the "Guideline for Carbon Emission Reduction Accounting of Solid Waste Resource Utilization Products," and the default carbon emission factor value is taken from the GB / T32151 series of standards.

[0107] Indirect carbon consumption is: C 间接 = in, W k Let k be the quality of the natural material that is being replaced. EF 替代,k This is the carbon emission factor of the material.

[0108] The amount of carbon credits from mineralized carbon sequestration is the sum of direct carbon consumption and indirect carbon consumption. C 矿化 =C 直接 +C 间接 Carbon credit deductions are included in the accounting results for revision. E 净 = E 总 - C 矿化 in, E 总This is the sum of emissions from all stages calculated in step four. E 净 This is the net emission amount after deducting mineralized carbon sinks.

[0109] Step Six: Carbon Emission Allocation of Co-existing Products Based on the symbiotic product allocation rules, the accounting results are distributed to various products such as alumina, silica, and mineral residues. The allocation rules support two models: economic value allocation and quality allocation.

[0110] Quality allocation method (applicable when products have similar economic value): F 产品,i = E 净 × in, M i Let be the quality of the i-th product.

[0111] Economic value allocation method (recommended method, applicable when product value differences are significant): F 产品,i = E 净 × in, V i Let be the economic value of the i-th product (market price × output).

[0112] The above allocation rules are formulated in accordance with the requirements of Clause 7.4.3 of ISO 14067:2018 "Greenhouse gases - Carbon footprint of products - Quantification requirements and guidance" regarding the allocation of symbiotic products. The economic value allocation method uses the product market price as the allocation weight, and the market data comes from publicly available industry quotations, based on the average price of the accounting year.

[0113] Step 7: Quantifying Uncertainty Based on the uncertainty of emission factors at each stage, the confidence interval of the carbon footprint results is calculated using an error propagation model: U 总 = in, U i Let be the relative uncertainty (%) of the i-th emission factor. w i The weight of this factor in total emissions, i.e. w i = .

[0114] The emission factor uncertainty Ui for each stage is taken according to the following reference values: pretreatment unit (crushing, grinding, drying): ±5%~±10%; fuel (natural gas, etc.) combustion emission factor: ±5%~±10%; power emission factor: ±5%~±8%; process reaction emission factor: ±10%~±20%; mineralization efficiency coefficient η: ±10%~±25%; residue mineralization treatment unit coefficient: ±8%~±12%.

[0115] The values ​​of Ui mentioned above are based on the following: The IPCC Guidelines for National Greenhouse Gas Inventories and Uncertainty Management are the basis for determining the uncertainty of fossil fuel combustion emission factors (±5%~±10%); the uncertainty of electricity emission factors (±5%~±8%) is based on the statistical fluctuation analysis of grid emission factors; the uncertainty of process emissions and mineralization efficiency (±10%~±25%) mainly comes from material composition fluctuations and industrial process amplification effects; the energy consumption emission uncertainty of pretreatment and residue mineralization units (±5%~±12%) combines the combined effects of electricity factor fluctuations and changes in material properties.

[0116] Step 8: Output the calculation results: Output the carbon footprint accounting results for the entire process chain, including: detailed emissions of each stage, deduction of mineralized carbon sinks, carbon footprint allocation values ​​of each product, confidence interval of the results, and generate a carbon footprint accounting report.

[0117] Second embodiment: This embodiment discloses a carbon footprint accounting device for the entire coal gangue process chain. It enables accurate carbon emission accounting, scientific carbon offsetting, reasonable allocation of carbon sinks for co-produced products, and precise correction of result errors throughout the entire coal gangue resource utilization process chain. This solves the technical problems of traditional accounting methods, such as ambiguous boundaries, single emission factors, low data accuracy, and lack of basis for carbon sink allocation. The device consists of an accounting boundary definition module, a differentiated emission factor database construction module, a full-process data acquisition and verification module, a sub-item carbon emission accounting module, a carbon offset calculation module, a co-produced product carbon sink allocation module, and an error analysis and result output module. These modules interact bidirectionally via a wired industrial bus and wireless IoT signals, forming a closed-loop carbon footprint accounting system. The specific implementation methods and connection relationships of each module are as follows.

[0118] Specific implementation of the accounting boundary delineation module: The accounting boundary definition module is the basic positioning module of the device, without any prior data dependency. It provides a standardized benchmark for the entire device's accounting scope and serves as the constraint carrier for the accounting scope of all other modules. In this embodiment, this module pre-fixes the standardized accounting boundary of the entire process chain of coal gangue resource utilization through programming. The boundary range fully covers the six core processes of coal gangue pretreatment, roasting and activation, acid and alkali leaching, alumina extraction, silica preparation, and residue mineralization treatment, while explicitly excluding non-production process links such as plant office and logistics support.

[0119] The module has pre-defined process node division standards to accurately define the start and end points of each process: the coal gangue pretreatment process covers raw material crushing, screening, and drying; the roasting and activation process covers calcination and activation under different atmospheres and temperatures; the acid-base leaching process covers acid dissolution, alkali dissolution, and solid-liquid separation; the alumina extraction process covers purification, crystallization, and calcination molding; the silica preparation process covers sol, gel, and drying modification; and the residue mineralization process covers solid waste proportioning, carbonization reaction, and residue molding and stacking. This module synchronously distributes the defined standardized accounting boundary parameters to the full-process data acquisition and verification module and the sub-item carbon emission accounting module, limiting the scope of subsequent data acquisition and carbon emission accounting to avoid over- or under-scope accounting.

[0120] Specific implementation of the differentiated emission factor database construction module: The differentiated emission factor database module is a core data support module for the device, independently completing database construction and updates, and providing accurate factor matching services for the sub-item carbon emission accounting module. In this embodiment, the module builds a dedicated differentiated emission factor database based on the IPCC National Greenhouse Gas Inventory Guidelines, the industry standard for carbon emission accounting of industrial solid waste resource utilization, and the differentiated characteristics of coal gangue resource utilization processes.

[0121] The database adopts a three-level classification storage architecture, and all emission factors are accurately classified and archived according to process characteristics: The first level is divided into three categories of factors according to the activation atmosphere type: air atmosphere, nitrogen inert atmosphere, and oxygen-enriched activation atmosphere; the second level is divided into three categories of factors according to the acid-base system type: hydrochloric acid leaching system, sulfuric acid leaching system, and sodium hydroxide alkali solution system; the third level is divided into three categories of factors according to the process temperature range: low temperature (200℃~500℃), medium temperature (500℃~800℃), and high temperature (800℃~1200℃).

[0122] Meanwhile, the database has a built-in factor update port, which can connect in real time to update factor parameters according to the latest industry carbon emission accounting standards, and each type of factor is bound to a corresponding process condition tag. This module establishes a one-way signal call connection with the sub-item carbon emission accounting module. The sub-item carbon emission accounting module can automatically match and retrieve the exclusive emission factors in the database according to the actual process conditions collected, replacing the traditional unified fixed factors and significantly improving the accounting accuracy.

[0123] Specific implementation of the end-to-end data acquisition and verification module: The end-to-end data acquisition and verification module is the core of the device's data input. It connects to the production site equipment, the plant's energy consumption metering system, and the material management system. It also receives process boundary instructions from the accounting boundary definition module, collects data only for the process links within the defined scope, and establishes a data output connection with the sub-item carbon emission accounting module.

[0124] In this embodiment, the module is equipped with an IoT data acquisition terminal, a smart meter, a material ledger sensor, and a mineralization process parameter detector to simultaneously collect multi-dimensional measured data across the entire process chain: energy consumption data for each process, such as electricity, coal, and natural gas; real-time dosage data for reagents such as hydrochloric acid, sulfuric acid, and sodium hydroxide; inventory ledger data for coal gangue raw materials, intermediate materials, co-produced products, and production residues; operating parameters of the mineralization process, such as reaction pressure, reaction time, and CO2 injection rate; and dynamic measured data for on-site equipment operating load and operating time.

[0125] The module has a built-in data normalization and verification algorithm to perform outlier removal, unit unification, time series calibration, and missing value completion on the collected raw data: it removes abnormal data that exceeds the normal operating range of the process, converts all energy consumption and material data into national standard units of measurement, calibrates the time series deviation of different equipment, completes short-term missing data by using the average of adjacent operating conditions, and finally outputs the measured data of the standardized activity level of each process. The verified valid data is then transmitted in real time to the sub-item carbon emission accounting module and the carbon sink deduction accounting module.

[0126] Specific implementation of the carbon emission accounting module: The sub-item carbon emission accounting module is the core carbon emission accounting unit. It establishes bidirectional signal connections with both the differentiated emission factor database module and the full-process data acquisition and verification module, and is the core computing module of the device. This module receives the measured data of standardized activity levels of each process transmitted by the full-process data acquisition and verification module. At the same time, based on the actual process conditions of each process (activation atmosphere, acid-base system, reaction temperature), it sends factor retrieval instructions to the differentiated emission factor database module to accurately match the specific direct and indirect emission factors of the corresponding process.

[0127] The specific calculation logic in this embodiment is as follows: direct carbon emission accounting focuses on direct carbon-generating links such as fuel combustion, chemical reactions of reagents, and tail gas emissions from mineralization processes; indirect carbon emission accounting focuses on indirect carbon-generating links such as purchased electricity, steam, reagent production, and material transportation. The module uses the core formula "activity level data × corresponding differentiated emission factor" to independently calculate the direct and indirect carbon emission values ​​for six major processes: coal gangue pretreatment, roasting activation, acid-base leaching, alumina extraction, precipitated silica preparation, and residue mineralization treatment. These values ​​are then summed to obtain the total original carbon emissions for the entire process chain. The results of the individual calculations and the total carbon emission data are then synchronously transmitted to the error analysis and result output module.

[0128] 5. Specific Implementation of the Carbon Credit Deduction Calculation Module The carbon sequestration deduction calculation module is a precise carbon sequestration calculation unit. It receives measured data from the mineralization process transmitted by the full-process data acquisition and verification module, and simultaneously establishes a data output connection with the co-production product carbon sequestration allocation module. The module has a built-in carbon sequestration calculation subroutine specifically adapted to the unique reaction characteristics of carbon sequestration and fixation of coal gangue residue.

[0129] In this embodiment, the module relies on the collected data on the calcium and magnesium content of coal gangue residue, the measured parameters such as mineralization reaction temperature and pressure, CO2 concentration, and reaction time, and combines them with the calculation formula for carbon sequestration efficiency of the mineralization reaction to calculate two types of carbon sequestration: one is direct carbon sequestration, which is the amount of carbon fixed by the carbonization reaction of calcium and magnesium ions in the residue with CO2 to form carbonates; the other is indirect carbon sequestration, which is the equivalent carbon emission reduction generated by waste heat recovery and energy consumption optimization to replace traditional fossil energy during the process. The module adds up the direct and indirect carbon sequestration to obtain the total carbon sequestration deduction of the entire coal gangue process chain, and simultaneously pushes the total carbon sequestration data and the detailed carbon sequestration data of each process to the carbon sequestration allocation module of the co-produced products.

[0130] 6. Specific Implementation of the Carbon Sequestration Allocation Module for Co-produced Products The carbon sink allocation module for co-produced products is a carbon sink equitable allocation unit. It receives the total carbon sink deduction data from the carbon sink deduction calculation module in one direction. After the calculation is completed, it transmits the allocation result to the error analysis and result output module to achieve accurate calculation of the net carbon footprint.

[0131] In this embodiment, the module incorporates a standardized allocation criterion for multi-product co-productions. It constructs a comprehensive allocation model using the product's output value share, material consumption share, and process energy consumption share as three-dimensional allocation weights, thus avoiding the bias issues associated with allocation based on a single weight. The specific allocation process is as follows: based on the market output value, production process material consumption, and process energy consumption share of the three co-production products—alumina, silica, and mineral residue—the comprehensive allocation weight for each product is calculated. The total carbon offset amount for the entire process chain is then precisely allocated to each type of co-production product according to its weight, resulting in a dedicated carbon offset amount for each product category. This provides a core basis for calculating the carbon footprint of a single product.

[0132] 7. Specific Implementation of Error Analysis and Result Output Module The error analysis and result output module is the terminal processing and output unit of the device. It receives the raw carbon emission data from the sub-item carbon emission accounting module and the product carbon sink allocation data from the co-production product carbon sink allocation module. It has a built-in error propagation analysis model and is the final node of the entire device's data closed loop.

[0133] In this embodiment, the error analysis process of the module is as follows: on the one hand, quantifying the operating condition adaptation deviation of the differentiated emission factors, comparing the subtle differences between the standard factors and the actual process conditions, and calculating the systematic error introduced by the factors; on the other hand, quantifying the acquisition fluctuations and verification fitting errors of the measured data throughout the entire process, and statistically analyzing the random errors in the data acquisition process. Through the error propagation algorithm, all error sources are integrated to define the credible confidence intervals of the carbon footprint accounting results for the entire process chain and each co-production product.

[0134] The final accounting process is as follows: the net carbon emissions are obtained by deducting the corresponding allocated carbon sink deduction from the original total carbon emissions of each process. Combined with the error confidence interval, the standardized accounting results are finally output, including the total carbon footprint of the entire process chain, the carbon footprint of each process, the carbon footprint of alumina / silica / mineralized residue as a single product, and the corresponding accounting error range, so as to achieve accurate, reliable and traceable accounting of the carbon footprint of the entire coal gangue process chain.

[0135] 8. Overall Coordination Workflow of the Device After the device is started, the accounting boundary definition module first locks the entire process accounting scope and issues boundary instructions; then the full-process data acquisition and verification module completes full-dimensional data acquisition and standardization processing within the boundary range; the sub-item carbon emission accounting module calls the exclusive factors of the differentiated emission factor database module and combines them with standardized data to complete the sub-item carbon emission accounting; at the same time, the carbon sink deduction accounting module completes the full-chain carbon sink accounting based on measured data and pushes the results to the co-production product carbon sink allocation module to realize the product carbon sink allocation; finally, all accounting data are summarized to the error analysis and result output module to complete error correction and result output. All modules are linked and coordinated in a closed loop throughout the process, with no accounting gaps or data deviations.

[0136] refer to Figure 4-Figure 4 As shown, the apparatus of the present invention will be further described in detail below with reference to embodiments: Accounting object: A certain high-alumina coal gangue silicon-aluminum extraction process (annual production of 10,000 tons of alumina and 8,000 tons of silica), which adopts oxygen-enriched atmosphere roasting activation + acid-base leaching + Bayer process for aluminum extraction + medium-temperature mineralization of residue.

[0137] The accounting boundary definition module determines the accounting boundary: referring to the requirements of T / CECA-G0334-2024, the accounting scope covers the entire process chain of coal gangue pretreatment, oxygen-enriched roasting activation, acid and alkali leaching, Bayer process aluminum extraction, white carbon black carbon fraction preparation, residue mineralization treatment and residue mineralization treatment, including the main production system, auxiliary production system and ancillary production system.

[0138] The differentiated emission factor database module collects activity data: Based on material and energy balance calculations, the activity data for each stage are as follows: Link Activity data numerical values Value description Coal gangue input Input 50,000t / a Pretreatment (crushing, grinding, drying) Electricity consumption 5 million kWh / a Estimated based on 100 kWh / t of coal gangue Calcination activation (oxygen-rich atmosphere) Electricity consumption 4.5 million kWh / a Estimated based on 90 kWh / t of coal gangue Natural gas consumption 2 million m³ / a Estimated based on 40 m³ / t of coal gangue Acid-base leaching Electricity consumption 1.5 million kWh / a Estimated based on 30 kWh / t of coal gangue NaOH consumption 850t / a Estimated at 1.7% of the coal gangue input. Steam consumption 32,000 GJ / a Estimated based on 0.64 GJ / t coal gangue Alumina extraction (Bayer process) Electricity consumption 12 million kWh / a Estimated based on 1200 kWh / tAl2O3 Preparation of silica Electricity consumption 1.6 million kWh / a An estimated 32 kWh / t of coal gangue. Residue mineralization Residue 32,000t / a Based on an estimated 64% of the coal gangue input... mineralization temperature 180℃ Process setting CO2 partial pressure 1.2MPa Process setting Residue mineralization treatment Electricity consumption 2.5 million kWh / a Estimate based on 50% of the pretreatment power consumption. Flocculant consumption 50t / a Estimate based on wastewater treatment scale The data for each of the above-mentioned stages were determined through engineering scale-up based on well-known material and energy balance methods in the field of silicon-aluminum extraction from coal gangue, combined with the process conditions (calcination temperature, liquid-solid ratio, reaction time, etc.) set in this embodiment. In practical applications, the data for each stage should be collected based on the actual metering results of the specific process unit.

[0139] The end-to-end data acquisition and verification module selects emission factors: Emission sources Emission factors Value illustrate Power grid National power grid average emission factor 0.5306 tCO2 / MWh Announcement No. 47 of 2025 issued by the Ministry of Ecology and Environment natural gas IPCC default value 2.176 kg CO2 / m³ The unit calorific value contains 15.3% carbon and has a carbon oxidation rate of 99%. NaOH preparation industry average 2.0tCO2 / t Average data for the caustic soda industry Flocculant preparation industry average 1.5tCO2 / t Default values ​​for chemical products The sub-item carbon emission accounting module calculates emissions at each stage: Pretreatment unit power emissions: 5 million kWh × 0.5306 = 265.3 tCO2; Electricity emissions from roasting activation: 4.5 million kWh × 0.5306 = 238.8 tCO2; Natural gas emissions: 2 million m³ × 2.176 kg / m³ ÷ 1000 = 435.2 tCO2; Acid-base leaching power emissions: 1.5 million kWh × 0.5306 = 79.6 tCO2; NaOH preparation emissions: 850 × 2.0 = 1700.0 tCO2; Alumina extraction for electricity generation: 12 million kWh × 0.5306 = 636.7 tCO2; The electricity emissions from the production of silica are: 1.6 million kWh × 0.5306 = 84.9 tCO2. Electricity emissions from residue mineralization treatment: 2.5 million kWh × 0.5306 = 132.7 tCO2; Flocculant preparation emissions: 50t × 1.5 = 75.0t CO2; Process reaction emissions (carbonate decomposition, etc.): approximately 820.0 tCO2; Total Emissions (E_total): =265.3+238.8+435.2+79.6+1700.0+84.9+636.7+132.7+75.0+820.0=4468.2tCO2; Conversion verification: 4468.2tCO2 ÷ 50,000t coal gangue ≈ 893.6kg / t coal gangue; Carbon credit calculation module, mineralized carbon credit calculation: The residue contains 18% active CaO and 6% active MgO. R carbon fixation = ×18%+ ×6%=0.1414+0.0660=0.2074; That is, the theoretical CO2 fixation rate is 207.4 kg / t residue; Mineralization conditions: temperature 180℃, CO2 partial pressure 1.2MPa, reaction time 3h. The efficiency coefficient η is 0.72 according to the table.

[0140] C_direct = 32,000 t × 0.2074 × 0.72 = 477.9 tCO2; Indirect carbon consumption: Mineralized residue replaces approximately 28,000 tons of natural building material raw materials, and the carbon emission factor for replacing cement is calculated at 0.8 tCO2 / t. Cindirect = 2.8 × 0.8 = 224.0 tCO2; Core = 477.9 + 224.0 = 701.9 tCO2; Carbon sequestration allocation module for co-produced products: Net emissions and product allocation: Net E = 4468.2 - 701.9 = 3766.3 tCO2; Using the economic value allocation method (alumina market price 3200 yuan / t, annual output value 32 million yuan; silica market price 1800 yuan / t, annual output value 14.4 million yuan; mineralized residue as building material auxiliary material, annual output value approximately 2 million yuan): Alumina carbon footprint: 3766.3×3200 / (3200+1440+200)= 2492.8 tCO2, unit product carbon footprint: 2492.8÷10000= 0.249tCO2 / t; Carbon footprint of white carbon black: 3766.3×1440 / (3200+1440+200)= 1121.6tCO2, carbon footprint per unit product: 1121.6÷8000= 0.140tCO2 / t; Error analysis and results output module, uncertainty quantification: Weight calculation of each stage (w) i =Emissions at this stage / Total emissions): Link Emissions (tCO2) weight wi Ui Preprocessing 265.3 0.059 ±8% Calcination activation (electric) 238.8 0.053 ±5% Natural gas combustion 435.2 0.097 ±6% Acid-base leaching (electricity) 79.6 0.018 ±5% NaOH preparation 1700 0.381 ±12% Alumina extraction (electricity) 636.7 0.143 ±5% Preparation of silica (electricity) 84.9 0.019 ±5% Residue mineralization treatment 207.7 0.046 ±10% Process reaction 820 0.184 ±15% total 4468.2 1.000 -- Carbon footprint results (95% confidence interval): alumina 0.249±0.014tCO2 / t, silica 0.140±0.008tCO2 / t.

[0141] As a preferred option: Accounting object: A process for extracting silicon and aluminum from low-alumina coal gangue (annual production of 0.5 million tons of alumina and 0.6 million tons of silica), which adopts an air atmosphere roasting activation + sulfuric acid pressurized acid leaching for aluminum extraction, and the residue is mineralized at room temperature.

[0142] Low-alumina coal gangue (Al2O3 content approximately 25%–28%, SiO2 content approximately 45%–50%) has low chemical activity, and sulfuric acid pressure leaching can effectively improve the alumina leaching rate. According to literature data, the alumina leaching rate under pressure leaching conditions can reach 95%–99%, which is superior to conventional atmospheric pressure leaching (approximately 79.6%–87%).

[0143] The accounting boundary delineation module determines the accounting boundaries: In accordance with the requirements of T / CECA-G0334-2024, the accounting scope covers the entire process chain of coal gangue pretreatment (crushing, grinding, drying), air atmosphere roasting and activation, sulfuric acid pressurized acid leaching for aluminum extraction, white carbon black carbon fraction preparation, residual room temperature mineralization treatment and residual mineralization treatment (wastewater treatment, waste gas treatment), including the main production system, auxiliary production system and ancillary production system.

[0144] The differentiated emission factor database module collects activity data. Based on material and energy balance calculations, the activity data for each stage are as follows: Link Activity data numerical values Source Explanation Coal gangue input Input 18,000t / a Annual production of Al2O3: 005,000 tons, based on an Al2O3 content of 28% and a leaching rate of 95%. Pretreatment (crushing, grinding, drying) Electricity consumption 1.8 million kWh / a Estimated based on 100 kWh / t of coal gangue Calcination activation (air atmosphere) Electricity consumption 1.35 million kWh / a Estimated based on 75 kWh / t of coal gangue Calcination activation (air atmosphere) Natural gas consumption 720,000 m³ / a Estimated based on 40 m³ / t of coal gangue Sulfuric acid pressure leaching (alumina extraction) Electricity consumption 1.2 million kWh / a Estimated based on the comprehensive power consumption of the leaching process Sulfuric acid pressure leaching (alumina extraction) Sulfuric acid consumption (98%) 468t / a The acid-to-slag ratio is approximately 1.3:1. Sulfuric acid pressure leaching (alumina extraction) Steam consumption 15,000 GJ / a Estimated based on the heat required at a reaction temperature of 150℃ Preparation of silica Electricity consumption 1.3 million kWh / a Combined power consumption for carbon removal, washing, and drying Residue mineralization treatment Electricity consumption 1.1 million kWh / a Neutralization treatment of acidic wastewater Residue mineralization treatment lime consumption 60t / a Estimate based on wastewater treatment scale Residue mineralization Residue 11,500t / a Based on an estimated 64% of the coal gangue input... Residue mineralization mineralization temperature 30℃ Process setting Residue mineralization <![CDATA[CO2 partial pressure]]> 0.6MPa Process setting The data for each of the above-mentioned stages were determined through engineering scaling based on well-known material and energy balance methods in the field of silicon-aluminum extraction from coal gangue, combined with the process conditions (acid-to-gangue ratio, reaction temperature, reaction time, etc.) set in this embodiment. In practical applications, the data for each stage should be collected based on the actual metering results of the specific process unit.

[0145] The end-to-end data acquisition and verification module selects emission factors: Emission sources Emission factors Value illustrate Power grid National average power emission factor 0.5306 tCO2 / MWh Announcement No. 47 of 2025 issued by the Ministry of Ecology and Environment natural gas IPCC default value 2.176 kg CO2 / m³ The unit calorific value contains 15.3% carbon and has a carbon oxidation rate of 99%. Sulfuric acid preparation industry average 0.10tCO2 / t (converted) Comprehensive emissions from coal-fired sulfuric acid production Lime preparation industry average 0.90tCO2 / t Limestone calcination emissions The sub-item carbon emission accounting module calculates the emissions at each stage; Pretreatment unit power emissions: 1.8 million kWh × 0.5306 = 95.5 tCO2; Electricity emissions from roasting activation: 1.35 million kWh × 0.5306 = 71.6 tCO2; Natural gas emissions: 720,000 m³ × 2.176 kg / m³ ÷ 1000 = 156.7 tCO2; Sulfuric acid production emissions: 468t × 0.10 = 46.8t CO2; Alumina extraction for electricity generation: 1.2 million kWh × 0.5306 = 63.7 tCO2; The electricity emissions from the production of silica are: 1.3 million kWh × 0.5306 = 69.0 tCO2; Electricity emissions from residue mineralization treatment: 1.1 million kWh × 0.5306 = 58.4 tCO2; Lime production emissions: 60t × 0.90 = 54.0t CO2; Process reaction emissions (carbonate decomposition, etc.): 210.0 tCO2; Total Emissions (E_total): =95.5+71.6+156.7+46.8+63.7+69.0+58.4+54.0+210.0=825.7tCO2 Conversion verification: 825.7tCO2 ÷ 18,000t coal gangue ≈ 458.7kg / t coal gangue.

[0146] Carbon credit calculation module, mineralized carbon credit calculation: The active CaO content in low-alumina coal gangue residue is approximately 12%, and the active MgO content is approximately 4%. R carbon fixation = ×12%+ ×4%=0.0943+0.0440= 0.1383; That is, the theoretical CO2 fixation rate is 138.3 kg / t residue.

[0147] Mineralization conditions: room temperature (30℃), CO2 partial pressure 0.6MPa, reaction time 6h, efficiency coefficient η = 0.42 obtained from the table.

[0148] C_direct = 11,500 t × 0.1383 × 0.42 = 66.8 t CO2; Indirect carbon consumption: Mineralized residue replaces approximately 0.95 million tons of natural building material raw materials, and the carbon emission factor for cement replacement is calculated at 0.8 tCO2 / t. Cindirect = 0.95 × 0.8 = 76.0 tCO2; C mineralization = 66.8 + 76.0 = 142.8 tCO2; Carbon sequestration allocation module for co-produced products: Net emissions and product allocation: Net E = 825.7 - 142.8 = 682.9 tCO2; Using the economic value allocation method (alumina market price 3200 yuan / t, annual output value 16 million yuan; silica market price 1800 yuan / t, annual output value 10.8 million yuan; mineralized residue annual output value approximately 700,000 yuan): Total economic value = 1600 + 1080 + 70 = 2750,000 yuan; Alumina carbon footprint: 682.9 × 1600 / 2750 = 397.4 tCO2; Carbon footprint per unit product: 397.4 ÷ 5000 = 0.079 tCO2 / t; Carbon footprint of white carbon black: 682.9 × 1080 / 2750 = 268.2 tCO2; Carbon footprint per unit product: 268.2 ÷ 6000 = 0.045 tCO2 / t; Error analysis and results output module, uncertainty quantification: Weighting of each stage (wi = emissions of that stage / total emissions): Link Emissions (tCO2) weight wi Uncertainty Ui Preprocessing 95.5 0.116 ±8% Calcination activation (electric) 71.6 0.087 ±5% Natural gas combustion 156.7 0.19 ±6% Sulfuric acid preparation 46.8 0.057 ±10% Alumina extraction (electricity) 63.7 0.077 ±5% Preparation of silica (electricity) 69 0.084 ±5% Residue mineralization treatment 112.4 0.136 ±10% Process reaction 210 0.253 ±15% total 825.7 1 — Carbon footprint results (95% confidence interval): Alumina: 0.079±0.003tCO2 / t; Silica: 0.045±0.002tCO2 / t.

[0149] The above are merely preferred embodiments of the present invention and do not limit the scope of the patent. Any equivalent structural or procedural transformations made based on the description and drawings of the present invention, or direct or indirect applications in other related technical fields, are similarly included within the scope of patent protection of the present invention.

Claims

1. A coal gangue full-process chain carbon footprint accounting method, characterized in that, Includes the following steps: Define standardized accounting boundaries, which cover the entire process chain of coal gangue pretreatment, roasting and activation, acid and alkali leaching, alumina extraction, precipitated silica preparation and residue mineralization treatment; Establish a differentiated emission factor database for the resource utilization of coal gangue, wherein the emission factors are classified according to the type of activation atmosphere, the type of acid-base system, and the process temperature range; Simultaneously collect energy consumption data, reagent dosage, material inbound and outbound ledgers, mineralization process operating parameters, and on-site dynamic measured data of the entire process chain, and complete data normalization and verification. Based on the measured data of standardized activity levels of each process in the entire process chain, the corresponding exclusive emission factors are matched, and the direct and indirect carbon emission values ​​of each production link are calculated separately. Construct a dedicated carbon sink calculation module for carbon mineralization, and calculate the total carbon sink deduction corresponding to direct and indirect carbon sequestration by combining the calcium and magnesium content of solid waste, mineralization reaction conditions and carbon dioxide fixation efficiency. Based on the standardized allocation criteria for co-produced products, the total carbon sink deduction calculated is allocated to various co-produced products such as alumina, silica, and mineral residues. An error propagation analysis model is introduced, which combines the statistical deviation of emission factors and the fluctuation error of measured data to carry out error propagation calculation on the accounting results of the entire process chain, quantifies the uncertainty and determines the credible confidence interval, and outputs the final carbon footprint data.

2. The coal gangue full-process-chain carbon footprint accounting method according to claim 1, characterized in that, When establishing the differentiated emission factor database for the resource utilization of coal gangue, the assignment methods include: Graded emission factors are set according to three types of roasting atmospheres: inert, oxidizing, and reducing. The reagent consumption and emission factors are matched according to the acidic and alkaline leaching systems; The process energy emission factor is corrected based on the low, medium and high temperature gradients.

3. The method for calculating the carbon footprint of the entire coal gangue production chain according to claim 2, characterized in that, The differentiated emission factor database covers the differentiated emission factors of six core process units: coal gangue pretreatment, roasting and activation, acid and alkali leaching, alumina extraction, precipitated silica preparation, and residue mineralization treatment. The pretreatment covers carbon emissions from electricity generation, and the roasting and activation are adapted to 25%~35% oxygen-enriched atmosphere and air atmosphere conditions; the acid and alkali leaching covers sources of electricity, reagents, and steam emissions; the alumina extraction is adapted to Bayer process and acid process; the precipitated silica preparation distinguishes between external flue gas and process tail gas carbon dioxide sources; the residue mineralization treatment covers carbon emissions from electricity and reagent preparation.

4. The method for calculating the carbon footprint of the entire coal gangue production chain according to claim 1, characterized in that, The direct carbon emissions include direct carbon emissions from fuel combustion, and the indirect carbon emissions include carbon emissions embodied in purchased energy. Among them, emissions from fuel combustion are calculated based on fuel consumption and specific emission factors, while carbon emissions from purchased electricity and heat are calculated based on corresponding benchmark emission factors and actual energy consumption.

5. The method for calculating the carbon footprint of the entire coal gangue production chain according to claim 1, characterized in that, In the process of constructing the carbon sink calculation module dedicated to carbon mineralization, the quantitative correlation between the calcium and magnesium content of the residue, mineralization conditions and carbon dioxide fixation rate was fitted by orthogonal experiments. The mineralization conditions include temperature, pressure, duration, and efficiency coefficient; the carbon sequestration amount is calculated based on the fitting formula, distinguishing between the direct carbon sequestration amount and the indirect emission reduction amount from auxiliary energy consumption, and completing the carbon sink deduction accounting.

6. The method for calculating the carbon footprint of the entire coal gangue production chain according to claim 5, characterized in that, The total carbon sink offset corresponding to the indirect carbon sequestration includes the emission reduction amount from the resource-based substitution of mineralized residues. The modified mineralized residues replace natural building materials and cementitious materials. Based on the carbon emission benchmark of the alternative materials, the emission reductions generated in the mining and processing of natural minerals are calculated.

7. The method for calculating the carbon footprint of the entire coal gangue production chain according to claim 1, characterized in that, The error propagation analysis model is constructed based on the weighted coupling uncertainty of each emission stage; The model predefines the standardized uncertainty thresholds for the emission factors of each core unit, wherein: fuel is 5%–10%, electricity is 5%–8%, process is 10%–20%, mineralization efficiency is 10%–25%, residue mineralization treatment is 8%–12%, and pretreatment is 5%–10%. The error propagation analysis model can realize the source tracing and sensitivity analysis of independent uncertainties in each process.

8. The method for calculating the carbon footprint of the entire coal gangue production chain according to claim 1, characterized in that, Based on the carbon sink calculation module and error propagation analysis model specifically designed for carbon mineralization, the carbon sink calculation results and error correction results are calibrated in a linked manner. Based on the total carbon emissions calculated across the entire process chain, the net carbon emissions of the coal gangue resource utilization process are obtained by deducting the carbon consumption from direct mineralization and the emission reduction from indirect resource utilization.

9. The method for calculating the carbon footprint of the entire coal gangue production chain according to claim 1, characterized in that, The carbon emission allocation of the symbiotic products follows the ISO14067:2018 international standard and is configured with three optional allocation modes: economic value allocation mode, quality allocation mode, and energy consumption allocation mode. The allocation calculation can be carried out by selecting one or combining them according to the project accounting needs.

10. A carbon footprint accounting device for the entire coal gangue production chain, characterized in that, It includes modules for defining accounting boundaries, building a database of differentiated emission factors, collecting and verifying data throughout the entire process, calculating carbon emissions by category, calculating carbon credits, allocating carbon credits for co-produced products, and analyzing errors and outputting results. The accounting boundary delineation module is used to define the standardized accounting boundary, which covers the entire process chain of coal gangue pretreatment, roasting activation, acid and alkali leaching, alumina extraction, precipitated silica preparation and residue mineralization treatment. The differentiated emission factor database module is used to establish a differentiated emission factor database for the resource utilization of coal gangue. The emission factors in the emission factor database are classified and stored according to the activation atmosphere type, acid-base system type and process temperature range for subsequent calculation and matching calls. The full-process data acquisition and verification module is used to synchronously collect energy consumption data, reagent dosage, material inbound and outbound ledgers, mineralization process operating parameters and on-site dynamic measured data of the entire process chain, and to perform data normalization verification on the collected data and output the measured data of the standardized activity level of each process. The sub-item carbon emission accounting module is connected to the differentiated emission factor database module and the full-process data acquisition and verification module, respectively. It is used to receive the measured data of the standardized activity level of each process, match the corresponding exclusive emission factors in the database, and calculate the direct and indirect carbon emission values ​​of each production link. The carbon sequestration deduction calculation module is equipped with a dedicated carbon sequestration calculation module for carbon mineralization, which combines the calcium and magnesium content of solid waste, mineralization reaction conditions and carbon dioxide fixation efficiency to calculate the direct carbon sequestration and indirect carbon sequestration respectively, and obtain the total carbon sequestration deduction of the entire process chain. The carbon sequestration allocation module for co-produced products is connected to the carbon sequestration deduction calculation module. It is used to allocate the total carbon sequestration deduction calculated to various co-produced products such as alumina, silica, and mineral residue according to the standardized allocation criteria for co-produced products. The error analysis and result output module has a built-in error propagation analysis model, which is used to combine the statistical deviation of emission factors and the fluctuation error of measured data to carry out error propagation calculation on the accounting results of the whole process chain, quantify the uncertainty and determine the credible confidence interval, and output the final carbon footprint data.

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