A carbon emission reduction accounting method for cement based on slag raw materials

Abstract

This invention discloses a carbon emission reduction accounting method for cement based on slag raw materials, belonging to the field of carbon emission reduction accounting technology. Specifically, it includes: acquiring mineral phase composition data and real-time calcination parameter data of slag raw materials; constructing a correlation model between slag activity and carbonization rate and generating a carbonization activity index; calculating the carbonization reaction process curve based on this index combined with slag fineness data and cement mix proportion data; collecting environmental status data of the cement product's usage environment and obtaining actual carbonization degree data through coupled calculations; calculating carbon dioxide sequestration data over the cement product's life cycle based on the actual carbonization degree data and slag incorporation data; and finally combining the carbon dioxide sequestration data with production process emission data to generate net carbon emission data. This invention achieves accurate quantification of the carbon footprint of cement based on slag raw materials, providing a reliable technical basis for carbon emission reduction in the cement industry.

Description

Technical Field

[0001] This invention relates to the field of carbon emission reduction accounting technology, and specifically to a carbon emission reduction accounting method based on slag cement. Background Technology

[0002] The cement industry is an energy- and resource-intensive industry and a major source of carbon emissions. Against the backdrop of global efforts to promote green and low-carbon development, utilizing industrial solid waste such as slag as cement raw materials or admixtures has become an important technological approach to reduce carbon emissions in the cement industry. By reducing the amount of traditional limestone raw materials and utilizing the potential cementitious activity of slag, certain emission reduction effects can be achieved at the source of production. However, to scientifically quantify this emission reduction contribution and ensure its recognition in carbon trading markets or green product certification, it is necessary to establish accurate and reliable carbon emission reduction accounting methods.

[0003] Currently, existing technologies in this field mainly revolve around accounting systems based on fixed emission factors. One typical approach uses a life cycle assessment framework, calculating the theoretical carbon emissions of cement products by setting a uniform slag replacement ratio and corresponding standard emission factors. Another approach focuses on the carbonization process of slag cement during its use phase, estimating the amount of carbon dioxide that may be fixed over its life cycle by using the carbonization rate constant measured under standard laboratory conditions combined with a simple linear model. These methods provide a basic framework for assessing the carbon footprint of slag cement.

[0004] However, existing accounting models generally rely on pre-set fixed emission factors and static environmental parameters, failing to establish a dynamic relationship between the inherent characteristics of slag raw materials and their carbonization reactivity exhibited in actual cement matrices. This results in the accounting process being unable to respond to the essential differences in carbonization capacity caused by variations in chemical composition, mineral phase composition, especially glass content, crystalline phase type and distribution, and thermal history (such as calcination temperature profiles and cooling regimes) of slag from different sources. Furthermore, existing methods oversimplify the consideration of the actual use environment of cement products, typically employing constant or regionally averaged environmental conditions (such as temperature, humidity, and carbon dioxide concentration), while ignoring the dynamic fluctuations of these factors over time and their complex interactions with the evolution of material microstructure (such as porosity changes and microcrack development). This dual neglect of the inherent variability of material properties and the dynamics of the external environment makes it difficult for accounting results based on such methods to accurately characterize the true carbon sequestration capacity and net carbon emission levels of slag-based cement products. Summary of the Invention

[0005] The purpose of this invention is to provide a carbon emission reduction accounting method for cement based on slag raw materials, and to solve the following technical problems:

[0006] Existing carbon emission reduction accounting methods cannot respond to the impact of differences in the composition and process of different slag raw materials on their carbonization activity. At the same time, they ignore the dynamic changes in actual environmental parameters and the interaction between the material's microstructure, resulting in inaccurate assessment of the carbon fixation capacity of slag raw material cement and making it difficult to support the needs of refined carbon accounting.

[0007] The objective of this invention can be achieved through the following technical solutions:

[0008] A carbon emission reduction accounting method for cement based on slag raw materials includes the following steps:

[0009] S1. Obtain mineral phase composition data of slag raw materials and real-time calcination parameter data during the production process;

[0010] S2. Based on mineral phase composition data and real-time calcination parameter data, establish a correlation model between slag raw material activity and carbonization rate, and generate a slag raw material carbonization activity index.

[0011] S3. Based on the carbonization activity index of slag raw materials, combined with the fineness data of slag raw materials and cement mix proportion data, calculate the carbonization reaction process curve of slag raw materials.

[0012] S4. Collect environmental status data of the environment in which the cement product is located throughout its life cycle, and couple the environmental status data with the carbonization reaction process curve to generate actual carbonization data.

[0013] S5. Based on the actual carbonation data and the data on the amount of slag raw materials incorporated into cement products, calculate the amount of carbon dioxide fixed by slag raw materials during the life cycle of cement products.

[0014] S6. Input the carbon dioxide fixation data into the carbon emission reduction accounting system, and combine it with the direct and indirect emission data in the cement production process to generate the net carbon emission data of slag raw material cement.

[0015] As a further aspect of the present invention: in step S2, the process of establishing a correlation model between the activity of slag raw materials and the carbonization rate is as follows:

[0016] The ratio of glassy phase content to crystalline phase content in the mineral phase composition data was analyzed. Combined with the calcination zone temperature and cooling rate data in the real-time calcination parameter data, the metastable structural strength parameters of the slag raw material were calculated. Based on the theoretical relationship between the metastable structural strength parameters and the activation energy of the carbonization reaction, the intrinsic kinetic equation of the carbonization reaction was established.

[0017] The oxygen partial pressure data and carbon monoxide concentration data from the flue gas composition data are input into the redox potential calculation function to obtain the calcination environment oxidative index; the pre-exponential factor in the intrinsic kinetic equation of the carbonization reaction is corrected using the calcination environment oxidative index to generate the carbonization activity index of the slag raw material.

[0018] As a further aspect of the present invention: in step S3, the process of calculating the carbonization reaction progress curve of the slag raw material is as follows:

[0019] The carbonization activity index of slag raw materials is decomposed into chemically active components and physically active components. The chemically active component is related to the intrinsic rate of carbonization reaction, and the physically active component is related to the ion diffusion and transport rate.

[0020] Based on the particle size distribution characteristics in the fineness data of slag raw materials, the specific surface area contribution weight of different particle size ranges is calculated. Combined with the water-cement ratio data and mineral admixture data in the cement mix proportion data, a porous media transport model is established.

[0021] By coupling chemically active components, physically active components, and porous media transport models, a multi-stage kinetic equation for the carbonization reaction is constructed. The multi-stage kinetic equation for the carbonization reaction is solved, and a carbonization reaction process curve including chemically controlled and diffusion-controlled stages is generated.

[0022] As a further aspect of the present invention: in step S4, the process of coupling the environmental state data with the carbonization reaction process curve is as follows:

[0023] The temporal fluctuation characteristics of carbon dioxide concentration data in environmental status data are monitored, and the peak concentration frequency data and duration data are extracted. The reaction driving force term in the carbonization reaction process curve is corrected based on the peak concentration characteristics.

[0024] Collect diurnal fluctuation data of ambient temperature, calculate the influence factor of temperature stress on the development of microcracks in cement matrix, and adjust the effective diffusion coefficient in the carbonation reaction process curve according to the influence factor of microcrack development.

[0025] Record the number of wet and dry cycles of relative humidity data, establish a pore structure evolution function, and simultaneously substitute the corrected reaction driving force term, the adjusted effective diffusion coefficient, and the pore structure evolution function into the carbonization reaction process curve to obtain the actual carbonization degree data through iterative calculation.

[0026] As a further aspect of the present invention: the process of establishing the pore structure evolution function is as follows:

[0027] Monitor the temporal changes of relative humidity data in environmental status data, and record the number of cycles of relative humidity data between above the saturation threshold and below the dryness threshold; collect the temporal changes of environmental temperature data, and calculate the average temperature data accompanying each relative humidity cycle.

[0028] A two-dimensional input vector containing relative humidity cycle number data and accompanying average temperature data is established. The two-dimensional input vector is input into a pre-trained pore network response model. The pore network response model outputs the theoretical most probable pore size data and theoretical porosity data under the current cycle number. Based on the change in the ratio of the theoretical most probable pore size data to the theoretical porosity data, the pore size-porosity correlation factor is calculated. The theoretical porosity data, the theoretical most probable pore size data, and the pore size-porosity correlation factor are combined to generate a pore structure evolution function.

[0029] As a further aspect of the present invention: In step S5, the process of calculating the carbon dioxide fixation data of slag raw materials during the life cycle of cement products is as follows:

[0030] Identify the structural type data and service stress state data of cement products; determine the number and location distribution of carbonation exposed surfaces based on the structural type data; calculate the promoting factor of stress level on carbonation rate based on service stress state data;

[0031] A three-dimensional carbonization front advancement model was established to simulate the transport path of carbon dioxide under stress. By combining actual carbonization degree data with the three-dimensional carbonization front advancement model, the spatiotemporal evolution volume of the carbonization reaction zone was calculated. Based on the spatiotemporal evolution volume of the carbonization reaction zone and the data on the amount of slag raw materials incorporated, the carbon dioxide fixation data during the life cycle of cement products was solved by integration.

[0032] As a further aspect of the present invention: the process of establishing the three-dimensional carbonization front propulsion model is as follows:

[0033] Geometric information is extracted from the design drawings of cement products. The geometric information includes component size data, protective layer thickness data and reinforcement layout data. The geometric information is discretized into a three-dimensional finite element mesh. Material property parameters are defined in the finite element mesh. The material property parameters include the carbonization activity index of slag raw materials, effective diffusion coefficient and carbon dioxide binding capacity.

[0034] Set boundary conditions, which include carbon dioxide concentration data, temperature data and relative humidity data from the environmental state data, solve the carbon dioxide transport-reaction partial differential equation system, obtain the numerical solution of the distribution of carbon dioxide concentration in three-dimensional space as a function of time, mark the grid cells where the carbon dioxide concentration reaches the carbonization threshold as carbonized regions, and output the advancement process of the carbonization front in three-dimensional space and the spatiotemporal evolution volume of the carbonization reaction zone.

[0035] As a further aspect of the present invention: in step S6, the process of generating net carbon emission data for slag raw material cement is as follows:

[0036] A carbon flow tracing model is established for each process in cement production. The carbon flow tracing model distinguishes between process chemical emission data and energy combustion emission data. In the process chemical emission data, emission data from carbonate decomposition and emission data from sulfide oxidation are separated. In the energy combustion emission data, emission data from fossil fuel combustion and emission data from biomass fuel combustion are distinguished.

[0037] Carbon dioxide fixation data is allocated to the corresponding accounting period according to a time function. The carbon flow tracing model is used to statistically analyze the direct and indirect emission data within the accounting period. The carbon dioxide fixation data allocated in the same period is deducted from the sum of the direct and indirect emission data to generate the net carbon emission data of slag cement.

[0038] The beneficial effects of this invention are:

[0039] This invention establishes a dynamic correlation model between slag raw material characteristics and carbonization activity, enabling precise response to changes in carbonization capacity caused by compositional differences and process fluctuations in slag from different sources. By coupling real-time monitored environmental parameters with a carbonization reaction kinetic model in multiple dimensions, it resolves the calculation bias caused by static environmental assumptions. Through constructing a multi-stage carbonization process model encompassing chemical activity and physical transport, it achieves a complete description of the carbonization reaction from the rapid stage to the diffusion-controlled stage. By introducing a three-dimensional carbonization front advancement model and a pore structure evolution function, it achieves spatial dynamic simulation of the carbon fixation capacity of cement products under actual usage conditions. By establishing a carbon flow tracking model that includes process chemical emissions and energy combustion emissions, and accurately calculating the carbon fixation amount over time, it ultimately provides net carbon emission data that truly reflects the characteristics of slag raw materials, differences in production processes, and dynamic changes in the usage environment, providing a reliable technical basis for the carbon trading market and green certification. Attached Figure Description

[0040] The invention will now be further described with reference to the accompanying drawings.

[0041] Figure 1 This is a flowchart illustrating the present invention. Detailed Implementation

[0042] 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 some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0043] Please see Figure 1As shown, this invention provides a carbon emission reduction accounting method for cement based on slag raw materials, comprising the following steps:

[0044] S1. Obtain mineral phase composition data of slag raw materials and real-time calcination parameter data during the production process;

[0045] S2. Based on mineral phase composition data and real-time calcination parameter data, establish a correlation model between slag raw material activity and carbonization rate, and generate a slag raw material carbonization activity index.

[0046] S3. Based on the carbonization activity index of slag raw materials, combined with the fineness data of slag raw materials and cement proportion data, calculate the carbonization reaction process curve of slag raw materials.

[0047] S4. Collect environmental status data of the environment in which the cement product is located throughout its life cycle, and couple the environmental status data with the carbonization reaction process curve to generate actual carbonization data.

[0048] S5. Based on the actual carbonation data and the data on the amount of slag raw materials incorporated into cement products, calculate the amount of carbon dioxide fixed by slag raw materials during the life cycle of cement products.

[0049] S6. Input the carbon dioxide fixation data into the carbon emission reduction accounting system, and combine it with the direct and indirect emission data in the cement production process to generate the net carbon emission data of slag raw material cement.

[0050] In a preferred embodiment of the present invention, the process of establishing a correlation model between the activity of slag raw materials and the carbonization rate in step S2 is as follows:

[0051] First, a complete diffraction pattern of the slag raw material was obtained using X-ray diffraction analysis. The Rietveld full-spectrum fitting method was then used to quantitatively analyze the content ratio of the glassy phase and the crystalline phase. Typical mineral phase composition data include key parameters such as the percentage of glassy phase, the percentage of calcium aluminum feldspar, and the percentage of magnesium silicate. These mineral phase data were obtained under standard laboratory conditions, with at least three parallel measurements performed on each sample, and the average value was used as the final input data.

[0052] Meanwhile, a temperature sensor network deployed at the production site collects real-time temperature change data from the rotary kiln's firing zone. This data is recorded once per second, forming a complete temperature curve for the firing zone. An infrared thermometer array installed at the cooler outlet continuously monitors the cooling process of the slag material, recording the entire cooling rate from the firing temperature to ambient temperature. This real-time calcination parameter data is transmitted to the central processing system via an industrial IoT gateway, establishing a timestamp-aligned relationship with the mineral phase composition data.

[0053] After obtaining complete mineral phase composition data and real-time calcination parameter data, the calculation process for the metastable structural strength parameter is initiated. This calculation is based on the ratio of glass content to crystalline phase content, combined with the integral area of ​​the calcination zone temperature curve and the differential characteristics of the cooling rate, to obtain the numerical value of the metastable structural strength parameter through a verified nonlinear mapping relationship. This parameter essentially reflects the non-equilibrium structural characteristics formed in the slag raw material during rapid cooling, and its value typically ranges from 0.5 to 2.3, depending on the raw material composition and process conditions.

[0054] Based on the obtained metastable structural strength parameters, a quantitative correlation model between the two is established by calling a pre-set carbonization reaction activation energy database. This model uses a lookup table interpolation algorithm to determine the carbonization reaction activation energy value corresponding to a specific metastable structural strength, and then constructs the intrinsic kinetic equation for the carbonization reaction. This equation fully describes the intrinsic laws governing the carbonization reaction between slag raw materials and carbon dioxide under ideal conditions.

[0055] Another key aspect of the implementation process is the quantitative assessment of the oxidizing properties of the calcination environment. Time-series data on the percentage of oxygen and carbon monoxide volume concentrations are obtained from a continuous flue gas monitoring device and processed using a dedicated redox potential calculation function. This function first calculates the ratio of oxygen partial pressure to carbon monoxide partial pressure, then incorporates a temperature compensation factor, and finally outputs a dimensionless oxidizing property index for the calcination environment. This index typically ranges from 0.8 to 1.5, reflecting the redox atmosphere characteristics during the calcination process.

[0056] Finally, the pre-exponential factor in the intrinsic kinetic equation of the carbonization reaction was corrected using the calcination environment oxidative index. The correction process employed linear interpolation, adjusting the pre-exponential factor according to a preset ratio based on the degree of deviation of the oxidative index from the baseline value of 1.0. Through this series of rigorous calculations, a carbonization activity index for slag raw materials with clear physical meaning was finally generated, serving as the fundamental input parameter for all subsequent calculations.

[0057] In another preferred embodiment of the present invention, the process of calculating the carbonization reaction progress curve of the slag raw material in step S3 is as follows:

[0058] The carbonization activity index of slag raw materials was characterized by decomposition, separating it into two independent components: a chemically active component and a physically active component. The chemically active component primarily reflects the chemical driving force of the slag raw material participating in the carbonization reaction, and its value is directly related to the intrinsic rate of the carbonization reaction. The physically active component characterizes the transport properties of ions within and between slag particles, controlling the diffusion process of the carbonization reaction. This decomposition was achieved using a pre-trained support vector machine model, which established a quantitative separation relationship between the two components based on extensive experimental data.

[0059] After obtaining the chemically and physically active components, the fineness data of the slag raw material is processed. The raw particle size distribution data provided by the laser particle size analyzer is divided into several continuous particle size intervals, such as typical ranges like 0 to 3 micrometers, 3 to 10 micrometers, and 10 to 30 micrometers. For each particle size interval, the system calculates its corresponding specific surface area contribution weight, based on the ratio of the volume percentage of each interval to the characteristic particle size. The specific surface area contribution weight accurately reflects the difference in the ability of particles of different sizes to provide reaction surface during the carbonization reaction.

[0060] Simultaneously, water-cement ratio data and mineral admixture data are retrieved from the cement mix design database. The water-cement ratio directly affects the initial pore structure of the cement matrix, while data on different types of mineral admixtures determine the types and contents of auxiliary cementitious materials within the system. Based on this data, a porous media transport model is constructed, which simulates the diffusion path and transport rate of carbon dioxide in the cement matrix using the finite element method. The model fully considers key structural parameters such as porosity, tortuosity, and connectivity, as well as their evolution during the hydration process.

[0061] The next key step is to couple the chemically active components, physically active components, and the porous media transport model. A multi-stage kinetic equation for the carbonization reaction is constructed. In the chemically controlled stage, this equation is primarily governed by the chemically active components, while in the diffusion-controlled stage, it is influenced by both the physically active components and the porous media transport characteristics. The transition between the two stages is automatically determined by the system, typically set at the point when the carbonization reaction depth reaches a characteristic critical value.

[0062] In the chemically controlled stage, the kinetic equations describe the decay of the reaction rate using an exponential function, with the chemically active component serving as the coefficient of the exponential term. In the diffusion-controlled stage, the equations are transformed into a partial differential form based on Fick's second law, where the physically active component determines the magnitude of the diffusion coefficient, and the porous media transport model provides the boundary and initial conditions. The equations for both stages maintain continuity and smoothness at the transition points, ensuring the physical plausibility of the entire process curve.

[0063] The constructed multi-stage kinetic equations for the carbonization reaction were solved using the fourth-order Runge-Kutta method, yielding a complete functional relationship between carbon dioxide uptake and time. An adaptive step-size strategy was employed during the solution process, automatically reducing the step size in regions of rapid reaction rate change to ensure computational accuracy. The resulting carbonization reaction progress curves clearly demonstrate the dynamic process of the carbonization reaction transitioning from a rapid chemically controlled stage to a slow diffusion-controlled stage, providing an accurate predictive basis for subsequent calculations of actual carbonization degree.

[0064] In another preferred embodiment of the present invention, the process of coupling the environmental state data with the carbonization reaction process curve in step S4 is as follows:

[0065] A continuous monitoring network for environmental status data is deployed. Gas concentration sensor arrays are installed at typical exposure locations on the concrete structure. These sensors record time-series data of carbon dioxide volume concentration fraction at a sampling frequency of 6 times per minute. Monitoring points are selected considering spatial representativeness, typically with 6 monitoring points arranged at different heights and orientations above the structure surface. The acquired concentration data are filtered using a moving average method before being stored in an environmental database.

[0066] Fluctuation characteristic parameters were extracted from continuous carbon dioxide concentration monitoring data. An abnormally high concentration event exceeding 150% of the background value was identified using a peak detection algorithm, and the duration, rise slope, and fall slope of each peak event were recorded. Simultaneously, the frequency of peak events per unit time was statistically analyzed to form a concentration peak frequency dataset. These characteristic parameters reflect the non-steady-state characteristics of environmental carbon dioxide supply and are directly related to the gas-phase reactant supply conditions of the carbonization reaction. Based on the product relationship between peak duration and frequency, a reaction driving force correction coefficient was established, which acts dimensionlessly on the reaction rate term in the carbonization reaction progress curve.

[0067] Ambient temperature data was acquired through a network of temperature sensors deployed inside and on the surface of the structure. The sensors recorded temperature values ​​four times per hour for over 30 consecutive days to obtain complete diurnal temperature fluctuation characteristics. The difference between the daily maximum and minimum temperatures was calculated to obtain a diurnal temperature fluctuation amplitude sequence. The rate of temperature change, particularly the occurrence of sudden temperature drops, was also recorded. This temperature fluctuation data was input into a specially developed microcrack risk assessment algorithm. This algorithm, based on thermoelastic theory, calculates the thermal stress distribution caused by the temperature gradient and, combined with a material tensile strength database, predicts the probability of microcrack initiation and propagation. The output is a microcrack development influencing factor, with a value ranging from 0.8 to 1.5, used to dynamically adjust the effective diffusion coefficient in the carbonization reaction process curve.

[0068] Relative humidity monitoring uses a capacitive humidity sensor to record the percentage of relative humidity twice per hour. Two key thresholds are set during data processing: a saturation threshold of 85% relative humidity and a dryness threshold of 45% relative humidity. A complete wet-dry cycle is recorded when the monitored data rises from below the dryness threshold to above the saturation threshold, or falls from above the saturation threshold to below the dryness threshold, within two consecutive sampling periods. The number of cycles per unit time is counted to form a wet-dry cycle frequency dataset.

[0069] The process of establishing the pore structure evolution function is based on a deep integration of environmental monitoring data and material response models. First, a two-dimensional input vector is constructed, containing the number of relative humidity cycles and the accompanying average temperature data. The first dimension of each vector represents the cumulative number of wet-dry cycles, and the second dimension represents the average temperature value within the corresponding cycle. These vectors are arranged in chronological order to form a time-series dataset describing the history of environmental effects.

[0070] The constructed two-dimensional input vector sequence is input into the pre-trained pore network response model. This model is based on a deep neural network architecture and consists of one input layer, three hidden layers, and one output layer. The input layer receives two-dimensional environmental parameters, the hidden layers process data features through a non-linear activation function, and the output layer generates two key pore parameters: the theoretical most probable pore size and the theoretical porosity. The theoretical most probable pore size is expressed in nanometers, and the theoretical porosity is expressed as a percentage.

[0071] The training process for the pore network response model utilized 5000 sets of accelerated laboratory test data, covering the pore structure evolution of different types of cement-based materials under various temperature and humidity cycling conditions. Model validation results show that the coefficient of determination between the predicted and measured values ​​exceeds 0.92, indicating that the model has reliable predictive capabilities.

[0072] Based on the theoretical most probable pore size data and theoretical porosity data output by the model, the trend of their ratio change is calculated. The pore size-porosity correlation factor is defined as the relative rate of change between the current ratio and the initial ratio. This factor reflects the coordinated change of material pore structure characteristic parameters under the influence of environmental factors; a value greater than 1 indicates that the pore size increases faster than the porosity, while a value less than 1 indicates the opposite trend.

[0073] A complete pore structure evolution function is constructed by combining theoretical porosity data, theoretical most probable pore size data, and pore size-porosity correlation factors. This function is expressed in triplets, recording the values ​​of three characteristic parameters at each time point. The function update frequency is consistent with the acquisition frequency of environmental monitoring data to ensure timely reflection of changes in material properties caused by environmental effects.

[0074] After completing all preparatory work, the coupled calculation process began. First, the modified reaction driving force term was introduced into the carbonization reaction process equation, and the coefficients of the concentration-dependent terms in the equation were adjusted. Then, the effective diffusion coefficient under environmental influence was obtained by multiplying the microcrack development influence factor by the basic diffusion coefficient. Finally, the pore structure evolution function was embedded into the transport model to update the pore structure parameters in the equation.

[0075] The coupled computation employs an iterative solution strategy. The calculation sequence for each time step is as follows: updating environmental parameters, correcting the reaction driving force, adjusting the diffusion coefficient, evolving the pore structure, and solving for the carbonization depth. The time step is set to 24 hours to match the statistical period of the environmental monitoring data. Each iteration uses the carbonization state of the previous moment as the initial condition, combined with the current environmental parameters, to calculate the new carbonization reaction process.

[0076] A convergence criterion is set during the iterative calculation process. When the rate of change of the predicted carbonization depth is less than 0.1% for three consecutive time steps, the calculation is considered to have reached a stable state, and the iteration process is terminated. Typically, 10 to 15 iterations are sufficient to obtain the actual carbonization degree data that meets the accuracy requirements.

[0077] The entire coupled calculation process achieved dynamic interaction between environmental monitoring data and material performance prediction. By real-time correction of the reaction driving force term, the impact of environmental carbon dioxide concentration fluctuations on the reaction rate was accurately reflected; by adjusting the effective diffusion coefficient, the microcrack development effect caused by temperature stress was reasonably considered; and by introducing a pore structure evolution function, the changes in transport paths caused by wet-dry cycles were scientifically described. This multi-level, multi-factor coupled calculation method ensures that the final actual carbonation data can truly reflect the performance evolution of cement products in complex usage environments.

[0078] In another preferred embodiment of the present invention, the process of calculating the carbon dioxide fixation data of slag raw materials during the life cycle of cement products in step S5 is as follows:

[0079] Comprehensive identification of the structural characteristics of cement products. Structural type codes are extracted from a Building Information Modeling (BIM) database. These codes are categorized into 12 main types according to international standards, including basic component types such as beams, slabs, columns, and walls. Each structural type corresponds to specific environmental exposure conditions, such as outdoor atmospheric zones, outdoor splash zones, and indoor dry zones, representing different service environments.

[0080] The processing of structural type data includes determining the spatial distribution characteristics of carbonization exposure surfaces. For plate members, two main exposure surfaces are typically considered; for beam-column members, four exposure surfaces are considered; and for wall members, one or two exposure surfaces are determined based on the actual support conditions. The location information of the exposure surfaces is recorded as three-dimensional spatial coordinates, and the orientation angle of each exposure surface is also labeled. This data is stored in matrix form and retrieved in subsequent calculations.

[0081] Service stress state data were acquired using structural analysis software. First, the design load combination was input, including basic values ​​for dead load, live load, wind load, and temperature load. Finite element analysis was used to obtain stress distribution cloud maps of the members, extracting the maximum principal stress and stress gradient data. For concrete compression members, the stress level was typically controlled between 0.3 and 0.5 times the axial compressive strength; for bending members, the tensile stress was controlled between 0.4 and 0.6 times the tensile strength. These stress data were converted into stress influence coefficients, with values ​​ranging from 0.9 to 1.3, reflecting the promoting or inhibiting effect of the stress state on the carbonation rate.

[0082] The process of establishing a three-dimensional carbonization front advancement model begins with the digital processing of geometric information. Precise dimensional data of the components are extracted from CAD design drawings, including basic dimensions such as length, width, and height, as well as detailed dimensions such as chamfers and openings. Protective layer thickness data is read from reinforcement drawings, recording the minimum distance from the outer surface of the reinforcing bars to the nearest exposed concrete surface; these data are typically controlled between 20 mm and 50 mm. Reinforcing bar layout data includes the diameter, spacing, and arrangement of the reinforcing bars, with the diameter of main reinforcing bars ranging from 12 mm to 32 mm and the diameter of stirrups ranging from 6 mm to 10 mm.

[0083] The geometric discretization process uses eight-node hexahedral elements for mesh generation. The element size is determined according to the accuracy requirements; a fine mesh of 1 mm is used around the reinforcing bars, while a standard mesh of 3 mm is used in other areas. Each element is assigned a unique number, and its spatial coordinates, material properties, and boundary condition identifiers are recorded. For typical structural members, the number of mesh elements ranges from 100,000 to 1,000,000, ensuring computational accuracy while controlling the computational scale.

[0084] The material property parameters were assigned based on experimental test data and theoretical models. Each grid cell was assigned three key material parameters: the slag raw material carbonization activity index, derived from the calculation results of step S2, ranging from 0.5 to 2.0; the effective diffusion coefficient, provided by the coupled calculations of step S4, on the order of 10⁻¹² to 10⁻¹⁰ m² / s; and the carbon dioxide binding capacity, determined through thermogravimetric analysis, expressed as the number of milligrams of carbon dioxide that can be fixed per gram of material, with typical values ​​between 50 and 200 milligrams per gram. These parameters were distributed across all grid cells as field variables.

[0085] Boundary conditions were set considering actual environmental effects. A carbon dioxide concentration boundary was applied to the exposed surface grid, with values ​​derived from monthly averages of environmental monitoring data, ranging from 0.03% to 0.1%. The temperature boundary used a weighted average of monitoring data, taking into account diurnal fluctuations. The relative humidity boundary varied depending on the exposure conditions; measured values ​​were used for outdoor exposed surfaces, while indoor exposed surfaces were adjusted to account for ventilation conditions. All boundary conditions were updated sequentially every 30 days.

[0086] The carbon dioxide transport-reaction partial differential equations were solved using the finite element method. The governing equations include diffusion, reaction, and source terms. The diffusion term coefficients represent the effective diffusion coefficients, the reaction term coefficients are related to the carbonization activity index, and the source terms are proportional to the carbon dioxide binding capacity. An implicit time integration scheme was used, with a time step of 7 days. The solution was iteratively solved within each time step until convergence. The convergence criterion was that the rate of change of the concentration field between adjacent iterations was less than 0.1%.

[0087] During the numerical solution process, the carbon dioxide concentration values ​​of all grid cells are recorded at each time step. When the concentration value of a cell reaches the carbonization threshold, that cell is marked as a carbonized region. The carbonization threshold is determined experimentally, generally between 0.01% and 0.05%, with the specific value depending on the chemical composition of the slag raw material. As the computation progresses, the boundary of the carbonized region forms a three-dimensional carbonization front, and the advancement of this front in space is fully recorded.

[0088] The spatiotemporal evolution volume of the carbonization reaction zone is calculated by statistically analyzing the total number of carbonized grid cells. The output of each time step includes a carbonization depth distribution map, a carbonization volume growth curve, and a carbonization front propagation velocity field. For typical cement components, the carbonization depth may reach 10 mm to 30 mm during a 50-year design service life, with the carbonization volume accounting for 5% to 20% of the total volume.

[0089] Based on the spatiotemporal evolution volume of the carbonization reaction zone and combined with data on the amount of slag raw material incorporated, an integral calculation of carbon dioxide fixation is performed. First, the carbonization volume is converted into the mass of slag raw material participating in the reaction, with the conversion factor being the slag raw material incorporation ratio multiplied by the material density. Then, based on the carbon dioxide fixation capacity per unit mass of slag raw material, the carbon dioxide fixation amount at each time step is calculated. Finally, numerical integration is performed over all time steps within the design service life to obtain the total carbon dioxide fixation data.

[0090] The integration calculation employs the Simpson numerical integration method, with the integration step size consistent with the time step of the finite element method calculation. The decay of the carbonization reaction rate over time is considered during the calculation; a smaller time step is used in the initial stage of carbonization, gradually increasing as the reaction rate slows down. For a 100-year life cycle analysis, typically 500 to 1000 time steps are required.

[0091] The entire computation process is executed on a parallel computing cluster, employing a domain decomposition method to distribute computational tasks across multiple computing nodes. The computation time for a typical component ranges from 2 to 6 hours, depending on the grid size and required computational accuracy. The results include curves showing the change in carbon dioxide sequestration over time, spatial distribution contour maps, and detailed data for key nodes. This data provides complete input parameters for subsequent carbon emission reduction accounting.

[0092] In another preferred embodiment of the present invention, the process of generating net carbon emission data for slag raw material cement in step S6 is as follows:

[0093] The cement production process is broken down into five main steps: raw material crushing, raw meal preparation, clinker calcination, cement grinding, and finished product packaging. Each step is equipped with independent energy metering equipment and a material balance system to record real-time data on electricity consumption, fuel consumption, and material flow.

[0094] The calculation of process chemical emissions focuses on two chemical processes: carbonate decomposition and sulfide oxidation. The percentages of calcium carbonate and magnesium carbonate content are obtained through raw material chemical analysis, and combined with clinker production data, the carbon dioxide emissions from carbonate decomposition are calculated. In a typical raw material mix, limestone accounts for approximately 75% to 85%, and approximately 0.52 tons of carbon dioxide are generated per ton of clinker produced. The calculation of sulfide oxidation emissions is based on the sulfur content analysis of the raw materials. By monitoring the sulfur content in the feed and the sulfur concentration in the flue gas, the amount of carbon dioxide converted from sulfide oxidation is determined. This portion of emissions typically accounts for 1% to 3% of total chemical emissions.

[0095] The calculation of energy combustion emissions data distinguishes between fossil fuels and biomass fuels. In the clinker calcination process, online calorific value analyzers are installed to monitor the calorific value parameters of fossil fuels such as pulverized coal and natural gas in real time, and fossil fuel combustion emissions are calculated in conjunction with fuel consumption. Simultaneously, biomass fuels that may be used, such as rice husks and sawdust, are measured separately and calculated using different carbon emission factors. The carbon emission factor for fossil fuel combustion is determined based on fuel elemental analysis; the typical emission factor for bituminous coal is 2.2 tons of carbon dioxide per ton of fuel, while the emission factor for biomass fuels is treated as zero carbon emissions.

[0096] The time allocation of carbon dioxide fixation data was modeled using an exponential decay function. Based on the characteristics of the carbonization reaction process curve, the total carbon dioxide fixation was allocated to each accounting period according to time weights. In the first five years after cement products were put into use, the allocation ratio was relatively high, accounting for approximately 30% to 40% of the total fixation; subsequently, it decreased year by year, reaching a cumulative allocation ratio of over 90% by year 50. The specific parameters of the allocation function were dynamically adjusted based on the carbonization activity index of the slag raw materials and environmental status data.

[0097] Direct emissions data for the accounting period are obtained by aggregating process chemical emissions and energy combustion emissions from each production step. Indirect emissions data include emissions from purchased electricity and emissions from raw material transportation. The electricity emission factor is determined based on the average emission level of the regional power grid, while transportation emissions are calculated based on transportation distance, load, and fuel type. Emission data for each accounting period are compiled according to actual production records to ensure the timeliness and accuracy of the data.

[0098] Net carbon emissions are calculated by offsetting current emissions against the allocated carbon dioxide sequestration for the current period. A monthly rolling accounting mechanism is established, updating cumulative emissions and sequestration allocation data monthly. At the end of the accounting period, a complete data report is generated, including direct emissions, indirect emissions, carbon dioxide sequestration, and net emissions. The data in the report are cross-validated, including material balance checks, energy balance analysis, and emission factor rationality assessments.

[0099] A complete data quality assurance system was established during implementation. Detailed traceability records were maintained for all raw data, including calibration certificates for measuring equipment, test reports, and operation logs. Key parameters such as emission factors and allocation coefficients had established reasonable ranges, and a review process was automatically triggered when data exceeded these preset ranges. The final net carbon emission data was accompanied by detailed explanations of data sources and calculation methods, ensuring the transparency and reliability of the accounting results.

[0100] The foregoing has provided a detailed description of one embodiment of the present invention, but this description is merely a preferred embodiment and should not be construed as limiting the scope of the invention. All equivalent variations and modifications made within the scope of the claims of this invention should still fall within the patent coverage of this invention.

Claims

1. A carbon emission reduction accounting method based on slag cement, characterized in that, Includes the following steps: S1. Obtain mineral phase composition data of slag raw materials and real-time calcination parameter data during the production process; S2. Based on mineral phase composition data and real-time calcination parameter data, establish a correlation model between slag raw material activity and carbonization rate, and generate a slag raw material carbonization activity index. S3. Based on the carbonization activity index of slag raw materials, combined with the fineness data of slag raw materials and cement proportion data, calculate the carbonization reaction process curve of slag raw materials. S4. Collect environmental status data of the environment in which the cement product is located throughout its life cycle, and couple the environmental status data with the carbonization reaction process curve to generate actual carbonization data. S5. Based on the actual carbonation data and the data on the amount of slag raw materials incorporated into cement products, calculate the amount of carbon dioxide fixed by slag raw materials during the life cycle of cement products. S6. Input the carbon dioxide fixation data into the carbon emission reduction accounting system, and combine it with the direct and indirect emission data in the cement production process to generate the net carbon emission data of slag raw material cement.

2. The carbon emission reduction accounting method based on slag cement as described in claim 1, characterized in that, In step S2, the process of establishing the correlation model between the activity of slag raw materials and the carbonization rate is as follows: The ratio of glassy phase content to crystalline phase content in the mineral phase composition data was analyzed. Combined with the calcination zone temperature and cooling rate data in the real-time calcination parameter data, the metastable structural strength parameters of the slag raw material were calculated. Based on the theoretical relationship between the metastable structural strength parameters and the activation energy of the carbonization reaction, the intrinsic kinetic equation of the carbonization reaction was established. The oxygen partial pressure data and carbon monoxide concentration data from the flue gas composition data are input into the redox potential calculation function to obtain the calcination environment oxidative index; the pre-exponential factor in the intrinsic kinetic equation of the carbonization reaction is corrected using the calcination environment oxidative index to generate the carbonization activity index of the slag raw material.

3. The carbon emission reduction accounting method based on slag cement as described in claim 1, characterized in that, In step S3, the process of calculating the carbonization reaction progress curve of the slag raw material is as follows: The carbonization activity index of slag raw materials is decomposed into chemically active components and physically active components. The chemically active component is related to the intrinsic rate of carbonization reaction, and the physically active component is related to the ion diffusion and transport rate. Based on the particle size distribution characteristics in the fineness data of slag raw materials, the specific surface area contribution weight of different particle size ranges is calculated. Combined with the water-cement ratio data and mineral admixture data in the cement mix proportion data, a porous media transport model is established. By coupling chemically active components, physically active components, and porous media transport models, a multi-stage kinetic equation for the carbonization reaction is constructed. The multi-stage kinetic equation for the carbonization reaction is solved, and a carbonization reaction process curve including chemically controlled and diffusion-controlled stages is generated.

4. The carbon emission reduction accounting method based on slag cement according to claim 1, characterized in that, In step S4, the process of coupling environmental state data with the carbonization reaction process curve is as follows: The temporal fluctuation characteristics of carbon dioxide concentration data in environmental status data are monitored, and the peak concentration frequency data and duration data are extracted. The reaction driving force term in the carbonization reaction process curve is corrected based on the peak concentration characteristics. Collect diurnal fluctuation data of ambient temperature, calculate the influence factor of temperature stress on the development of microcracks in cement matrix, and adjust the effective diffusion coefficient in the carbonation reaction process curve according to the influence factor of microcrack development. Record the number of wet and dry cycles of relative humidity data, establish a pore structure evolution function, and simultaneously substitute the corrected reaction driving force term, the adjusted effective diffusion coefficient, and the pore structure evolution function into the carbonization reaction process curve to obtain the actual carbonization degree data through iterative calculation.

5. The carbon emission reduction accounting method based on slag cement according to claim 4, characterized in that, The process of establishing the pore structure evolution function is as follows: Monitor the temporal changes of relative humidity data in environmental status data, and record the number of cycles of relative humidity data between above the saturation threshold and below the dryness threshold; collect the temporal changes of environmental temperature data, and calculate the average temperature data accompanying each relative humidity cycle. A two-dimensional input vector containing relative humidity cycle number data and accompanying average temperature data is established. The two-dimensional input vector is input into a pre-trained pore network response model. The pore network response model outputs the theoretical most probable pore size data and theoretical porosity data under the current cycle number. Based on the change in the ratio of the theoretical most probable pore size data to the theoretical porosity data, the pore size-porosity correlation factor is calculated. The theoretical porosity data, the theoretical most probable pore size data, and the pore size-porosity correlation factor are combined to generate a pore structure evolution function.

6. The carbon emission reduction accounting method based on slag cement according to claim 1, characterized in that, In step S5, the process of calculating the carbon dioxide fixation data of slag raw materials during the life cycle of cement products is as follows: Identify the structural type data and service stress state data of cement products; determine the number and location distribution of carbonation exposed surfaces based on the structural type data; calculate the promoting factor of stress level on carbonation rate based on service stress state data; A three-dimensional carbonization front advancement model was established to simulate the transport path of carbon dioxide under stress. By combining actual carbonization degree data with the three-dimensional carbonization front advancement model, the spatiotemporal evolution volume of the carbonization reaction zone was calculated. Based on the spatiotemporal evolution volume of the carbonization reaction zone and the data on the amount of slag raw materials incorporated, the carbon dioxide fixation data during the life cycle of cement products was solved by integration.

7. The carbon emission reduction accounting method based on slag cement according to claim 6, characterized in that, The process of establishing the three-dimensional carbonization front advancement model is as follows: Geometric information is extracted from the design drawings of cement products. The geometric information includes component size data, protective layer thickness data and reinforcement layout data. The geometric information is discretized into a three-dimensional finite element mesh. Material property parameters are defined in the finite element mesh. The material property parameters include the carbonization activity index of slag raw materials, effective diffusion coefficient and carbon dioxide binding capacity. Set boundary conditions, which include carbon dioxide concentration data, temperature data and relative humidity data from the environmental state data, solve the carbon dioxide transport-reaction partial differential equation system, obtain the numerical solution of the distribution of carbon dioxide concentration in three-dimensional space as a function of time, mark the grid cells where the carbon dioxide concentration reaches the carbonization threshold as carbonized regions, and output the advancement process of the carbonization front in three-dimensional space and the spatiotemporal evolution volume of the carbonization reaction zone.

8. The carbon emission reduction accounting method based on slag cement according to claim 1, characterized in that, In step S6, the process of generating net carbon emission data for slag-based cement is as follows: A carbon flow tracing model is established for each process in cement production. The carbon flow tracing model distinguishes between process chemical emission data and energy combustion emission data. In the process chemical emission data, emission data from carbonate decomposition and emission data from sulfide oxidation are separated. In the energy combustion emission data, emission data from fossil fuel combustion and emission data from biomass fuel combustion are distinguished. Carbon dioxide fixation data is allocated to the corresponding accounting period according to a time function. The carbon flow tracing model is used to statistically analyze the direct and indirect emission data within the accounting period. The carbon dioxide fixation data allocated in the same period is deducted from the sum of the direct and indirect emission data to generate the net carbon emission data of slag cement.

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