Carbon emission evaluation method for converter smelting with high cold charge ratio

Abstract

The application provides a converter high-cool-material-ratio smelting carbon emission evaluation method, and relates to the metallurgy field. The method comprises the following steps: collecting the mass and carbon content data of all carbon-containing materials in a converter smelting period, and calculating the total carbon input C in ; collecting the mass and carbon / carbon oxide content of all carbon output items in the converter smelting period, and calculating the total carbon output C out ; establishing a balance model between the total carbon input C in and the total carbon output C out : C in =C out +ΔC, wherein ΔC is a model correction parameter; based on the balance model and the carbon output tracking data, the direct carbon emission of the converter steelmaking process is calculated; and the indirect emission caused by energy consumption is combined to comprehensively calculate the carbon emission intensity per ton of steel. The method provided by the application is suitable for the complex scene of mixed use of multiple varieties of cool materials, improves the evaluation accuracy, and provides quantifiable decision support for steel enterprises to optimize scrap steel utilization and reduce smelting carbon consumption.

Description

Technical Field

[0001] This application relates to the field of metallurgy, and more particularly to a method for assessing carbon emissions from converter smelting with a high cold charge ratio. Background Technology

[0002] As a major carbon-emitting industry, the steel industry urgently needs to transform towards green and low-carbon practices. Converter steelmaking is a core process in long-process steel production and a significant source of carbon emissions for steel companies. Increasing the proportion of cold iron-containing raw materials such as scrap steel and direct reduced iron in converter smelting is one of the most direct and effective technical pathways to reduce dependence on high-carbon-emission molten iron and lower the carbon emission intensity per ton of steel at its source.

[0003] Currently, for carbon emission accounting in converter processes, the industry generally adopts the "emission factor method" based on material and energy balance or default values ​​published by the state / industry. However, these traditional methods have revealed significant limitations and inadequacies in high cold charge ratio smelting modes, mainly reflected in: (1) Carbon flow tracking distortion: Traditional methods usually simplify carbon input to molten iron carbon and a small amount of added carbon. They do not adequately consider the large fluctuations in carbon input brought in by cold iron-containing raw materials with high proportions and multiple varieties (such as heavy scrap steel, light and thin materials, socially recycled scrap steel, direct reduced iron, etc.) or use fixed empirical coefficients, resulting in inaccurate carbon input source data.

[0004] (2) Increased complexity of carbon output pathways: Under high cold charge ratios, the thermodynamic state of the molten pool changes, and the carbon-oxygen reaction kinetics differ from those of conventional hot metal-dominated operation modes. The distribution patterns of carbon in molten steel, slag, flue gas (CO / CO2 ratio), and dust change accordingly. Traditional accounting models fail to dynamically reflect these changes in carbon migration characteristics, leading to biases in the accounting of carbon emission sources.

[0005] (3) Insufficient model adaptability: Most existing carbon emission accounting models are based on conventional molten iron ratios (such as 80%-90%). Their built-in parameters and balance relationships are no longer applicable under extreme or atypical working conditions with high cold material ratios (such as cold material ratios >20% or even higher). The calculation results cannot truly reflect the actual effect of process changes on carbon emission reduction, and it is difficult to support accurate carbon footprint diagnosis and process optimization.

[0006] Therefore, developing a method that can accurately track the complex carbon flow during high cold charge ratio converter smelting and conduct refined carbon emission assessments is of vital importance for steel companies to scientifically assess the carbon emission reduction benefits of scrap steel utilization, optimize low-carbon smelting processes, and achieve precise carbon asset management. Summary of the Invention

[0007] The purpose of this application is to provide a carbon emission assessment method for converter smelting with a high cold charge ratio, in order to solve the above-mentioned problems.

[0008] To achieve the above objectives, this application adopts the following technical solution: A method for assessing carbon emissions from converter smelting with a high cold charge ratio includes: Collect the mass and carbon content data of all carbon-containing materials during the converter smelting cycle, and calculate the total carbon input C. in ; Collect the mass and carbon / carbon oxide content of all carbon output items during the converter smelting cycle, and calculate the total carbon output C. out ; Based on the principle of conservation of matter, the total carbon input C is established. in With the total carbon output C out The balance model between: C in =C out +ΔC, where ΔC is the model correction parameter; Based on the aforementioned balance model and carbon output tracking data, the direct carbon emissions of the converter steelmaking process are calculated; and combined with the indirect emissions generated by energy consumption, the carbon emission intensity per ton of steel is comprehensively calculated. The calculation of ΔC satisfies the following conditions: ΔC=ΔC real + L d + L g ; ΔC real =ΔC reg +α(T−T target )+β(R−R opt )+γln([CO][CO2]; ΔC reg =k0+k1R c +k2C hot +k3K O2 +ε; L d =λm dust C dust ; L g =μV gas ∑(C CHx ); Where, ΔC real ΔC is a process correction parameter. reg These are the preset model calibration parameters, where T is the molten pool temperature. target The target molten pool temperature is 1600-1680℃; R is the slag basicity. opt The target slag basicity is set at 2.5-4; α, β, and γ are real-time correction coefficients, and L... d For losses due to the escape of extremely fine dust, L gFor trace hydrocarbons that were not detected, λ and μ are loss coefficients, where λ ranges from 0.001 to 0.01 and μ ranges from 0.01 to 0.1; m dust For dust quality, C dust V represents the average carbon content of the dust. gas C represents the volume of the flue gas. CHx denoted as , where is the carbon equivalent concentration of various hydrocarbons; k0, k1, k2, and k3 are regression coefficients, determined by least squares fitting; ε is the residual term, with a value less than 0.001; R0 c For cold material ratio, C hot The carbon content of molten iron, K O2 The oxygen blowing intensity.

[0009] Preferably, , Let the mass of the i-th carbon-containing raw material be _____. Let be the carbon content of the i-th carbon-containing material. It is the ratio of the relative molecular masses of carbon dioxide to carbon. Preferably, , Let the mass of the i-th carbon-containing solid be physicist. Let m be the carbon content of the i-th carbon-containing solid material. g For the physical mass of carbon-containing gases, This represents the carbon dioxide content in a carbon-containing gas. The content of carbon monoxide in a carbon-containing gas. This is the ratio of the relative molecular masses of carbon dioxide to carbon monoxide.

[0010] Preferably, the ΔC also satisfies the following condition: The ΔC also satisfies the following condition: .

[0011] Preferably, the direct carbon emissions are The indirect carbon emissions are The carbon emission intensity per ton of steel is E=E direct +E indirect ,in, To capture and utilize carbon dioxide from carbon-containing gases, Let i be the amount of the i-th type of energy medium consumed during the smelting process. is the carbon emission factor of the i-th energy medium consumed during the smelting process.

[0012] Preferably, the carbon-containing dust in the carbon output item includes smoke and splashes, and its carbon output is obtained by collecting dust samples for analysis or by using an empirical coefficient method based on material balance.

[0013] Preferably, the indirect emissions include indirect carbon emissions generated from electricity, oxygen, and natural gas consumed during the smelting process.

[0014] Preferably, the total carbon input C in and the total carbon output C out The expression is standardized based on the atomic weight converted into equivalent carbon dioxide.

[0015] Preferably, the carbon emission assessment method for converter high cold charge ratio smelting further includes: based on the carbon emission intensity per ton of steel and the total carbon input C in The total carbon output C out The impact of key process parameters on carbon emissions was analyzed.

[0016] Preferably, the key process parameters include cold material ratio, molten iron carbon content, oxygen consumption, and final molten steel carbon content.

[0017] Preferably, in the evaluation method, the converter cold charge ratio is not less than 20%.

[0018] Compared with the prior art, the beneficial effects of this application include: The carbon emission assessment method for high cold charge ratio smelting in converters provided in this application establishes a complete multi-source carbon input inventory (especially covering various types of fluctuating cold-state iron-containing raw materials) and uses a combination of actual measurement and predictive models to obtain accurate carbon content, ensuring data accuracy from the source. Simultaneously, the equilibrium model parameter ΔC is specifically calibrated for the characteristics of the high cold charge ratio, and the distribution of carbon in molten steel, slag, flue gas, and dust is meticulously tracked, dynamically reflecting the special laws of carbon migration under this operating condition, thus achieving a qualitative leap from "rough estimation" to "precise measurement." Furthermore, by accurately assessing the carbon emission reduction benefits of the high cold charge ratio, this method provides clear quantitative evidence for steel enterprises to maximize the utilization of scrap steel as a green raw material, encouraging enterprises to increase scrap steel utilization rates, thereby reducing dependence on high-carbon-footprint molten iron. This not only directly reduces carbon emissions per ton of steel but also lowers raw material costs and enhances the green competitiveness of enterprise products, achieving a win-win situation for both environmental and economic benefits. Attached Figure Description

[0019] To more clearly illustrate the technical solutions of the embodiments of this application, the accompanying drawings used in the embodiments will be briefly described below. It should be understood that the following drawings only show some embodiments of this application and should not be regarded as a limitation on the scope of this application.

[0020] Figure 1 This is a schematic flowchart of the carbon emission assessment method for converter high cold charge ratio smelting provided in the example. Detailed Implementation

[0021] To better illustrate the technical solution provided in this application, the technical solution will be described in its entirety before the embodiments, as follows: A method for assessing carbon emissions from converter smelting with a high cold charge ratio includes: S1: Collect the mass and carbon content data of all carbon-containing materials during the converter smelting cycle, and calculate the total carbon input C. in ; Carbon-containing materials constitute a complete carbon input list, specifically including: Metallic carbon sources: molten iron, and one or more cold-state iron-containing raw materials, including but not limited to scrap steel (heavy scrap steel, light scrap steel, recycled scrap steel, etc.), cold-pressed briquettes, pig iron blocks, and direct reduced iron; Auxiliary carbon sources: coke, coal, carbon powder, biomass, etc., added to adjust the temperature and composition of the molten pool; Alloy and auxiliary carbon sources: carbon-containing alloys (such as high-carbon ferromanganese, ferrosilicon) and other carbon-containing auxiliary materials (lime, dolomite, etc.). The total carbon input C is calculated by accurately weighing the mass of each material and obtaining its corresponding carbon content data. in .

[0022] S2: Collect the mass and carbon / carbon oxide content of all carbon output items during the converter smelting cycle, and calculate the total carbon output C. out ; This step enables the tracking of carbon output. For example, it can specifically involve: monitoring and classifying all carbon outflow paths during the smelting process, covering all carbon output items, including: product carbon fixation: dissolved carbon in the final molten steel (final carbon); by-product carbon fixation: carbon contained in the slag; gaseous carbon stream: carbon-containing gases in the converter flue gas; and carbon-containing dust: carbon carried in the fumes and splashes generated during the smelting process.

[0023] S3: Based on the principle of conservation of matter, establish the total carbon input C. in With the total carbon output C out The balance model between: C in =C out +ΔC, where ΔC is the model correction parameter; The parameter ΔC is not a simple error term, but a key parameter specifically set and corrected for the smelting characteristics of high cold charge ratios. A high cold charge ratio alters the molten pool heating pattern, slag formation process, and carbon-oxygen reaction kinetics, potentially causing unmeasured carbon losses (such as the escape of extremely fine dust) or measurement system bias. Determining ΔC relies on regression analysis of extensive historical furnace data for high cold charge ratios, as well as a mechanistic understanding of carbon migration characteristics under this condition, enabling the general equilibrium model to accurately adapt to this specific production mode.

[0024] S4: Based on the balance model and carbon output tracking data, the direct carbon emissions of the converter steelmaking process are calculated; and combined with the indirect emissions generated by energy consumption, the carbon emission intensity per ton of steel is calculated comprehensively.

[0025] Based on the corrected balance model and detailed data from carbon output tracking, a hierarchical carbon emission accounting system (direct carbon emissions and carbon emission intensity) is implemented.

[0026] Direct carbon emissions accounting: The core of this method is calculating the amount of carbon dioxide emitted as a greenhouse gas. This calculation involves extracting the total CO2 output monitored from the flue gas and deducting any CO2 subsequently captured and utilized. CO in the flue gas is typically used in other processes and is therefore not included in direct carbon emissions.

[0027] Here, the following parts need to be accurately identified from the total CO2 in the flue gas: (1) CO2 that can be recycled in subsequent processes; (2) Trace carbon species (such as CH4 and C2H6) that are not monitored in the flue gas are converted into CO2 equivalents through a stoichiometric model, which is also one of the key parts for determining ΔC.

[0028] Carbon emission intensity calculation: The calculated direct carbon emissions are summed with the indirect carbon emissions (calculated using recognized emission factors) corresponding to all energy media consumed during the smelting process, such as electricity, oxygen, natural gas, and compressed air, to obtain the total carbon emissions for that heat. Finally, this total carbon emissions are divided by the qualified steel production rate for that heat to obtain the core assessment indicator—carbon emission intensity per ton of steel.

[0029] The calculation of indirect carbon emissions requires real-time acquisition and normalization of energy consumption data, which involves the integration of data interfaces from multiple control systems (such as PLC, DCS, and MES). Furthermore, the construction and updating of the emission factor library requires the integration of multiple sources of factors, including national / industry standards, regional power grid factors, and enterprise measured data. Measured values ​​or values ​​provided by upstream industries should be the preferred source for carbon emission factors. For carbon emission factors that cannot be measured or cannot be provided by upstream industries, default values ​​provided by the region / country should be selected.

[0030] The calculation of ΔC satisfies the following conditions: ΔC=ΔC real + L d + L g ; ΔC real =ΔC reg +α(T−T target )+β(R−R opt )+γln([CO][CO2]; ΔC reg =k0+k1R c +k2C hot+k3K O2 +ε; L d =λm dust C dust ; L g =μV gas ∑(C CHx ); Where ΔC real ΔC is a process correction parameter. reg These are the preset model calibration parameters, where T is the molten pool temperature. target The target molten pool temperature is 1600-1680℃; R is the slag basicity. opt The target slag basicity is set at 2.5-4; α, β, and γ are real-time correction coefficients, and L... d For losses due to the escape of extremely fine dust, L g For trace hydrocarbons that were not detected, λ and μ are loss coefficients, where λ ranges from 0.001 to 0.01 and μ ranges from 0.01 to 0.1; m dust For dust quality, C dust V represents the average carbon content of the dust. gas C represents the volume of the flue gas. CHx denoted as , where is the carbon equivalent concentration of various hydrocarbons; k0, k1, k2, and k3 are regression coefficients, determined by least squares fitting; ε is the residual term, with a value less than 0.001; R0 c For cold material ratio, C hot The carbon content of molten iron, K O2 The oxygen blowing intensity.

[0031] The calculation principle of the above formula is as follows: First, based on a comprehensive analysis of the carbon loss pathway, the total correction ΔC is decoupled into three relatively independent parts: ΔC real This refers to the correction of the main process. It reflects the carbon content deviation within the main smelting reaction zone, caused by process conditions deviating from ideal or standard conditions, and can be dynamically described by key process variables. d With L g For escape and undetected losses. As an additional item, it specifically quantifies carbon losses that are inevitable due to the limitations of monitoring technology (such as the inability to collect all extremely fine dust or the incomplete detection of trace hydrocarbons by standard flue gas analyzers) but are difficult to accurately capture by the master process model.

[0032] ΔC real The core derivation principle is as follows: Under high cold feed ratio conditions, the carbon input source and oxidation environment undergo fundamental changes. Analysis of extensive historical production data reveals that the cold feed ratio R... c Initial carbon content (C) of molten ironhot Oxygen blowing intensity K O2 It is the most significant and stable presupposition factor affecting systemic carbon changes. Therefore, a multiple linear regression model ΔC is adopted. reg =k0+k1R c +k2C hot +k3K O2 The regression coefficients k0, k1, k2, and k3 are determined by fitting historical data using the least squares method, representing the contribution weights of each factor to the baseline carbon deviation. ε represents the statistical residual.

[0033] Furthermore, even under the same pre-set conditions, the molten pool temperature T, slag basicity R, and reaction atmosphere ([CO] / [CO2]) will fluctuate in actual smelting, directly affecting the kinetics and thermodynamic equilibrium of the carbon oxidation reaction.

[0034] α(T−T target This represents the temperature deviation. Temperature directly affects the reaction rate and gas solubility; deviations from the target temperature may lead to incomplete or excessive carbon oxidation.

[0035] β(R−R opt The basicity deviation term is represented by . Slag basicity affects the oxidizability and fluidity of the slag, thereby influencing the carbon transport behavior between slag and gold.

[0036] γln([CO][CO2]) represents the gas phase composition. The ratio of CO to CO2 in the flue gas is a key thermodynamic indicator reflecting the degree and pathway of carbon-oxygen reaction in the molten pool. Its logarithmic form is often related to the Gibbs free energy of the reaction and is used to correct for differences in carbon distribution caused by changes in the reaction pathway.

[0037] Therefore, ΔC real =ΔC reg +α(T−T target )+β(R−R opt The formula )+γln([CO][CO2] achieves a composite correction of "preset benchmark + real-time feedback", enabling the model to dynamically respond to process fluctuations.

[0038] L d With L g The core derivation principle is as follows: In the high-temperature flue gas of a converter, some extremely fine particulate matter (e.g., particles <10μm in diameter) may escape from conventional dust removal systems and be overlooked. The carbon loss it carries is proportional to the total amount of dust collected. dust The average carbon content (C) of dust dust Proportional. Therefore, model L is established. d =λm dust C dustThe loss coefficient λ can be calibrated using dust particle size distribution data and dust removal efficiency model, representing the proportion of the escaped portion.

[0039] During the smelting of complex scrap steel, trace amounts of hydrocarbons (such as CH4, C2H6, etc.) may be generated and emitted, while standard flue gas analysis primarily focuses on CO and CO2. This carbon loss is related to the total flue gas volume V. gas and the total carbon equivalent concentration of various hydrocarbons ∑(C CHx Proportional to ( ). Model L g =μV gas ∑(C CHx The loss coefficient μ is used to estimate this value and can be calibrated based on comparative experiments of specific hydrocarbon detections or more sophisticated gas chromatography-mass spectrometry analysis data.

[0040] Measured values: T is the molten pool temperature, R is the slag basicity, m dust For dust quality, C dust V represents the average carbon content of the dust. gas C represents the volume of the flue gas. CHx The carbon equivalent concentrations of various hydrocarbons are represented by Rc, where Rc is the cold feed ratio and C is the carbon equivalent concentration of each hydrocarbon. hot The carbon content of molten iron, K O2 The oxygen blowing intensity.

[0041] Theoretical value or range: T target The target molten pool temperature, depending on the steel grade, is typically between 1600-1680℃, R opt The target slag basicity is usually determined based on the phosphorus content of the molten iron and the dephosphorization requirements, and is typically between 2.5 and 4. ε is the residual term, which is close to 0. λ and μ are loss coefficients. λ mainly depends on the dust removal efficiency. Based on the current common dust removal efficiency in steel plants, λ is usually taken as 0.001-0.01. μ mainly depends on the amount of heat-replenishing agent. Based on experience, μ is usually taken as 0.01-0.1.

[0042] No fixed values: α, β, and γ are real-time correction coefficients, representing the sensitivity of temperature, alkalinity, and atmosphere to the carbon balance. Initial values ​​can be obtained through mechanistic model derivation or sensitivity analysis of historical data. Subsequent online updates and corrections are performed in practical applications using model adaptive techniques (such as Kalman filtering and least squares recursion). However, data is typically unique for each converter, and even converters with identical furnace types may exhibit significant differences in values. k0, k1, k2, and k3 are regression coefficients, entirely dependent on historical production data specific to the converter (furnace volume, furnace type), raw material conditions (molten iron composition, cold charge type), and operating procedures (oxygen supply, slag formation). These coefficients are obtained through fitting using statistical methods such as multiple linear regression.

[0043] In an optional implementation, the ΔC also satisfies the following condition: In one optional implementation, , Let the mass of the i-th carbon-containing raw material be _____. Let be the carbon content of the i-th carbon-containing material. It is the ratio of the relative molecular masses of carbon dioxide to carbon.

[0044] In one optional implementation, , Let the mass of the i-th carbon-containing solid be physicist. Let m be the carbon content of the i-th carbon-containing solid material. g For the physical mass of carbon-containing gases, This represents the carbon dioxide content in a carbon-containing gas. The content of carbon monoxide in a carbon-containing gas. This is the ratio of the relative molecular masses of carbon dioxide to carbon monoxide.

[0045] In an optional implementation, the ΔC also satisfies the following condition: .

[0046] In one optional implementation, the direct carbon emissions are The indirect carbon emissions are The carbon emission intensity per ton of steel is E=E direct +E indirect ,in, To capture and utilize carbon dioxide from carbon-containing gases, Let i be the amount of the i-th type of energy medium consumed during the smelting process. is the carbon emission factor of the i-th energy medium consumed during the smelting process.

[0047] In one optional embodiment, the cold iron-containing raw material in the carbon-containing material includes one or more of scrap steel, cold-pressed briquettes, pig iron, and direct reduced iron.

[0048] In an optional implementation, the total carbon input C is calculated. in For molten iron and / or the aforementioned cold iron-containing raw materials, measured carbon content data or carbon content prediction model data based on historical smelting data are used.

[0049] In one optional implementation, the carbon-containing gases in the carbon output item are continuously monitored by an online flue gas analysis system to obtain the concentration and volume percentage of carbon monoxide and carbon dioxide, as well as the total flue gas flow rate, and then the carbon output is calculated.

[0050] In an optional implementation, the carbon-containing dust in the carbon output item includes soot and splashes, and its carbon output is obtained by collecting dust samples for analysis or by using an empirical coefficient method based on material balance.

[0051] In one alternative implementation, the indirect emissions include indirect carbon emissions generated from the electricity, oxygen, and natural gas consumed during the smelting process.

[0052] In an optional implementation, the total carbon input C in and the total carbon output C out The expression is standardized based on the atomic weight converted into equivalent carbon dioxide.

[0053] In an optional implementation, the carbon emission assessment method for converter high cold charge ratio smelting further includes: based on the carbon emission intensity per ton of steel and the total carbon input C... in The total carbon output C out The impact of key process parameters on carbon emissions was analyzed.

[0054] Based on the quantitative data pool accumulated in steps S1 to S4, statistical methods were used to identify key emission links and analyze the influence and sensitivity of key process parameters on carbon emission intensity per ton of steel. Based on the sensitivity analysis results, the following optimization suggestions were generated: (1) Raw material structure optimization: Recommend the best ratio scheme of cold materials such as scrap steel and direct reduced iron; (2) Oxygen supply system adjustment: Recommend the optimization setting of oxygen lance position, flow rate and timing; (3) Energy system synergy: Propose systematic carbon reduction paths such as green electricity procurement, waste heat recovery and CO2 capture.

[0055] In one optional implementation, the key process parameters include the cold material ratio, the carbon content of molten iron, the oxygen consumption, and the carbon content of the final molten steel.

[0056] In an optional implementation, the converter cold charge ratio in the evaluation method is not less than 20%.

[0057] The implementation schemes of this application will be described in detail below with reference to specific embodiments. However, those skilled in the art will understand that the following embodiments are only for illustrating this application and should not be regarded as limiting the scope of this application. Unless otherwise specified in the embodiments, conventional conditions or conditions recommended by the manufacturer shall apply. Reagents or instruments used without specified manufacturers are all conventional products that can be purchased commercially.

[0058] Example 1 like Figure 1As shown, a steel plant's 150-ton converter plans to implement a low-carbon smelting mode, increasing the average cold charge ratio from the traditional 15% to 30%. To accurately assess the carbon emissions under this mode and guide process optimization, the carbon emission assessment method provided in this application is adopted, including the following steps: S1: Carbon Input Quantification The carbon-containing materials and their carbon content are shown in Table 1.

[0059] The molten iron was sampled and analyzed using a rapid temperature measurement instrument in front of the furnace, and the carbon content was measured to be 4.63%.

[0060] The heavy scrap steel was modeled using the plant's historical data, and its average carbon content was predicted to be 0.27%.

[0061] Direct reduced iron has a fixed carbon content of 1.8% according to the supplier's quality certificate.

[0062] According to the incoming inspection report, the fixed carbon content of the coke is 86%.

[0063] According to the incoming test report, the lime has a carbon content of 0.46%.

[0064] According to the incoming inspection report, the carbon content of the lightly calcined dolomite is 2.4%.

[0065] High-carbon ferromanganese, with a carbon content of 6.5% (according to standard composition).

[0066] Ferrosilicon, with a carbon content of 0.2% (according to standard composition).

[0067] Table 1. Carbon-containing materials and carbon content in the input items.

[0068] Total carbon input C in =30.08t S2: Carbon Export Tracking Sampling and analysis were performed at the end of the steel smelting process, and the final carbon content was 0.08%.

[0069] The final residue sample was collected and tested; the final carbon content was 0.3%.

[0070] The dust is calculated using the empirical coefficient for this process, with an average carbon content of 17.8%.

[0071] The splashed slag is calculated using the empirical coefficient for this process, with an average carbon content of 6.3%.

[0072] The converter gas volume, measured by the online laser gas analysis system installed in the flue, was 18794.1 m³. 3 The volume fraction of CO was 53.21%, and the volume fraction of CO2 was 22.01%.

[0073] Table 2. Output items: carbon-containing materials and carbon content

[0074] Total carbon output C out =29.99t, S3: Equilibrium model construction and calibration.

[0075] C in -C out =0.09t This difference primarily stems from potential minor leaks in the online flue gas monitoring system, the failure to account for the escape of extremely fine dust (<10μm), and the fact that some carbon elements exist in trace forms such as methane but are not completely captured by the analyzer. For this plant, the cold feed ratio is ~30%, the carbon content of the molten iron is 4.63%, and the oxygen supply intensity is 3.8m³. 3 Regression analysis of historical data for the (min·t) working condition was used to determine... k 0, k 1, k 2, k 3, e The values ​​are 0.13, 0.07, -1.1, 0.013, and 0.0005, respectively. The calculated model correction parameter ΔC is then obtained. reg =0.13+0.07×0.3-1.1×0.0463×0.013×3.8+0.0005=0.15.

[0076] Based on the target temperature T targrt =1660℃, actual tapping temperature 1658℃, target slag basicity 3.0, actual basicity 2.89, converter gas CO volume fraction 53.21%, CO2 volume fraction 22.01%, real-time correction coefficients α, β, γ for this heat are 0.15, 0.98, -0.076 respectively, determine ΔC real =0.15+0.15×(1658-1660)+0.98×(2.89-3)-0.076ln(0.5321×0.2201)=0.093.

[0077] Loss coefficient l , m They are respectively ， The dust concentrations are 0.00086 and 0.046, the dust mass is 13.14 kg / t steel, the average carbon content of the dust is 17.8%, and the flue gas volume is 119.86 m³. 3 / t steel, with a carbon equivalent concentration of 0.09% for various hydrocarbons. Calculate the escape loss of extremely fine dust. L d =0.00086×13.14×0.178=0.002, trace hydrocarbon loss was not detected. Lg =0.046×119.86×0.0009=0.005, therefore ΔC=0.093+0.002+0.005=0.1tC in ≈C out +ΔC, error r=|30.08-(29.99+0.1)| / 30.08=0.03%<1%, the model is in equilibrium and can be used for subsequent verification.

[0078] S4: Carbon emission accounting.

[0079] The plant lacks a carbon dioxide capture and utilization process, therefore it directly emits carbon E. direc =m g =Converter gas production × CO2 volume fraction in converter gas × 44 ÷ 22.4 = 18794.1 × 22.01% × 44 ÷ 22.4 = 8.13 tCO2 The direct carbon emission per ton of steel is 0.0518tCO2 / t steel.

[0080] The plant's consumption of electricity, oxygen, and other energy media, along with their carbon emission factors, and the resulting indirect carbon emissions are shown in Table 3. The indirect carbon emissions are 0.0537 tCO2 / t steel. The carbon emission factor for electricity is derived from the default value for electricity carbon emission factors published by the state for the region where the plant is located that year, while the others are derived from actual measured values ​​within the plant area.

[0081] Table 3 Indirect Carbon Emission Calculation Table

[0082] Carbon emission intensity per ton of steel = direct carbon emissions + indirect carbon emissions = 0.0518 + 0.0537 = 0.1055 tCO2 / t steel.

[0083] S5: Generate evaluation results and perform optimization analysis Under the 30% cold charge ratio, the total carbon input for this heat was 30.08 t, and the total carbon output (including ΔC) was 30.09 t, with good material balance (error 0.03%). The calculated carbon emission intensity per ton of steel was 0.1055 tCO2 / t steel, of which: direct emissions were 0.0518 tCO2 / t steel, accounting for 49.1%, and indirect emissions were 0.0537 tCO2 / t steel, accounting for 50.9%. Under the current cold charge ratio, the proportion of direct carbon emissions is slightly high. Appropriately increasing the cold charge ratio (such as adding 10% direct reduced iron) can effectively reduce carbon emissions. If the converter gas carbon dioxide is captured and utilized, direct carbon emissions can be significantly reduced. For indirect carbon emissions, carbon emissions from oxygen consumption contribute the most, accounting for 47.1% of total indirect emissions, followed by electricity consumption, accounting for 40.4%. Optimizing oxygen supply practices, such as adjusting oxygen gun positions and flow rates, can reduce oxygen consumption and thus reduce indirect carbon emissions. Purchasing green electricity and lowering the grid emission factor can also reduce carbon emissions from electricity consumption.

[0084] Example 2 A steel plant uses a 210-ton converter for high cold charge ratio smelting (50% cold charge ratio). To accurately assess carbon emissions under this model and guide process optimization, the carbon emission assessment method provided in this application is adopted, including the following steps: S1: Carbon Input Quantification The carbon-containing materials and their carbon content are shown in Table 4.

[0085] The molten iron was sampled and analyzed using a rapid temperature measurement instrument in front of the furnace, and the carbon content was measured to be 4.74%.

[0086] The heavy scrap steel was modeled using the plant's historical data, and its average carbon content was predicted to be 0.27%.

[0087] The average carbon content of the light and thin scrap steel is predicted to be 0.34% based on the plant's historical data model.

[0088] Direct reduced iron has a fixed carbon content of 2.0% according to the supplier's quality certificate.

[0089] According to the incoming inspection report, the fixed carbon content of the coke is 83%.

[0090] According to the incoming test report, the lime has a carbon content of 0.71%.

[0091] According to the incoming inspection report, the carbon content of the lightly calcined dolomite is 2.1%.

[0092] Ferrosilicon, with a carbon content of 0.2% (according to standard composition).

[0093] Table 4. Input items: carbon-containing materials and carbon content

[0094] Total carbon input Cin =67.77t S2: Carbon Export Tracking Sampling and analysis were performed after the steel smelting was completed, and the final carbon content was 0.07%.

[0095] The final residue sample was collected and tested, and the final carbon content was 0.42%.

[0096] The dust is calculated using the empirical coefficient for this process, with an average carbon content of 19.4%.

[0097] The splashed slag is calculated using the empirical coefficient for this process, with an average carbon content of 8.8%.

[0098] The converter gas volume, measured by the online laser gas analysis system installed in the flue, is 35913.6 m³. 3 The volume fraction of CO was 59.21%, and the volume fraction of CO2 was 30.31%.

[0099] Table 5. Carbon-containing materials and carbon content in the output items

[0100] Total carbon output C out =67.05t, S3: Equilibrium model construction and calibration.

[0101] C in -C out =0.72t This difference mainly stems from potential minor leaks in the online flue gas monitoring system, the failure to account for the escape of extremely fine dust (<10μm), and the fact that some carbon elements exist in trace forms such as methane but are not completely captured by the analyzer. Regression analysis of historical data from the plant under operating conditions of high cold charge ratio (~50%), molten iron carbon content of 4.74%, and oxygen supply intensity of 3.15 determined that… k 0, k 1, k 2, k 3, e The values ​​are 0.59, 0.08, -0.7, 0.02, and 0.0002, respectively. The calculated model correction parameter ΔC is... reg =0.59 + 0.08 × 0.5 - 0.7 × 0.0474 + 0.02 × 3.15 + 0.0002 = 0.66, Based on the target temperature T targrt =1660℃, actual tapping temperature 1649℃, target slag basicity 3.0, actual basicity 3.22, converter gas CO volume fraction 59.21%, CO2 volume fraction 30.31%, real-time correction coefficients α, β, γ for each heat are 0.03, 1.16, -0.055 respectively. Determine ΔC.real =0.66+0.03×(1649-1660)+1.16×(3.22-3)-0.055ln(0.5921×0.3031)=0.68.

[0102] Loss coefficient l , m They are respectively ， The dust concentrations are 0.0022 and 0.059, the dust mass is 16.26 kg / t steel, the average carbon content of the dust is 19.4%, and the flue gas volume is 169.2 m³. 3 / t steel, with a carbon equivalent concentration of 0.13% for various hydrocarbons. Calculate the escape loss of extremely fine dust. L d =0.0022×16.26×0.194=0.007, trace hydrocarbon loss was not detected. L g =0.059×169.2×0.0013=0.013, therefore ΔC=0.68+0.007+0.013=0.70t C in ≈C out +ΔC, error r=|67.77-(67.05+0.70)| / 67.77=0.03%<1%, the model is in equilibrium and can be used for subsequent verification.

[0103] S4: Carbon emission accounting.

[0104] The plant has a carbon dioxide capture and utilization process, which can capture and utilize an average of 88.91% of CO2. Therefore, direct carbon emissions E direc = m g - =35913.6×30.31%×44÷22.4×(1-88.91%)=2.37tCO2 The direct carbon emission per ton of steel is 0.0011tCO2 / t steel.

[0105] The consumption of electricity, oxygen, and other energy media, as well as the carbon emission factor, of the plant, and the indirect carbon emission calculated from these, are shown in Table 6. The indirect carbon emission is 0.0839 tCO2 / t steel. The carbon emission factor for electricity is from the default value of the national electricity carbon emission factor for the region where the plant is located in that year, and the rest are from actual measured values ​​at the plant site.

[0106] Table 6 Indirect Carbon Emission Calculation Table

[0107] Carbon emission intensity per ton of steel = direct carbon emissions + indirect carbon emissions = 0.0011 + 0.0839 = 0.0850 tCO2 / t steel.

[0108] S5: Generate evaluation results and perform optimization analysis Under the extremely high cold charge ratio mode of 50%, the carbon emission intensity per ton of steel is 0.0850 tCO2 / t steel. The proportion of direct emissions in the total emission intensity drops sharply to only 1.3%, while the proportion of indirect emissions is as high as 98.7%, which is completely different from the mode of traditional converters that are mainly based on direct emissions. This is because the plant has implemented advanced CO2 capture technology with a capture rate of up to 88.91%, which is the primary reason for the reduction of direct emissions to an extremely low level.

[0109] Electricity consumption contributes the most to indirect carbon emissions, accounting for 49.6% of total emissions. This is because carbon dioxide capture consumes a significant amount of electricity, but the carbon emissions generated by the extra electricity consumption are significantly lower than the carbon emissions reduced by carbon dioxide capture. This plant successfully transformed its converter from a "chemical process emission source" to an "energy consumption emission source" through a combination of "ultra-high cold charge ratio + carbon capture" technology. The main challenge shifted from reducing reliance on molten iron and optimizing steelmaking reactions to reducing the electricity consumption of high-energy-consuming auxiliary systems. For example, optimizing oxygen supply and adjusting oxygen lance position and flow rate can reduce oxygen consumption and thus indirect carbon emissions. Purchasing green electricity and lowering the grid emission factor can reduce carbon emissions generated from electricity consumption.

[0110] Comparative Example 1 To illustrate the superiority of the method in this application compared with traditional methods, and in comparison with Example 1, carbon emission assessment was conducted using the traditional carbon emission factor method (fixed coefficient method) commonly used in the industry under similar cold material ratio (approximately 30%) at the same steel plant and the same converter (150 tons), and the results were compared with those of the method in this application.

[0111] Traditional methods are usually based on fixed emission factors or empirical coefficients, without considering the dynamic allocation of carbon in multiple pathways, and mainly rely on the following simplified assumptions: (1) Carbon input only considers molten iron and a small amount of added carbon, and the carbon input of cold materials adopts a fixed average coefficient; (2) The main carbon emission is CO2 in flue gas, which is directly estimated using a fixed conversion rate (such as 85%); (3) Indirect carbon emissions use the industry average emission factor, without considering process coupling and differences in energy structure.

[0112] The same furnace production data as in Example 1 (raw material inputs such as molten iron, scrap steel, and direct reduced iron, and steel production, etc.) are used, but the following traditional processing method is adopted in carbon emission accounting: S1: Carbon input quantification (simplified); Carbon content in molten iron: 4.5% (a common industry experience value); Carbon content of cold materials (scrap steel, direct reduced iron): a fixed coefficient of 0.3% is uniformly adopted; The carbon content of the auxiliary materials is negligible.

[0113] calculate: C in =119.52×4.5%+(34.15+17.07)×0.3%=5.38+0.15=5.53t.

[0114] S2: Carbon Export Tracking (Simplified); Final carbon content of molten steel: 0.08% (actual measurement); Carbon in slag, dust, and splashes was not tracked separately and was uniformly classified as "unmetered carbon loss," with a fixed loss rate of 5%. Flue gas CO2 emissions are estimated using a simplified carbon balance method: C out,CO2 =C in ×85%=4.70t; C out,其他 =C in ×5%=0.28t; C out,钢水 =156.8 × 0.08% = 0.13t; C out =4.7 + 0.28 + 0.13 = 5.11t; S3: Model building (without dynamic correction); Traditional methods lack a dynamic correction parameter ΔC and directly use: C in =C out The error is (5.53-5.11) / 5.53=7.6%, which is relatively large.

[0115] S4: Carbon emission accounting (simplified factor method); Direct carbon emissions: E direct =4.70×44 / 12=17.23tCO2 Indirect carbon emissions: Using the nationally published industry average factor: Electricity: 0.6205 tCO2 / MWh × 0.035 MWh / t steel = 0.0217 tCO2 Oxygen: 0.4019 tCO2 / km 3 ×0.063km 3 / t steel = 0.0253t CO2 Other media ignored Total indirect emissions: 0.0470 tCO2 / t Carbon emission intensity per ton of steel: E = 17.23 / 156.80 + 0.0470 = 0.1099 + 0.0470 = 0.1569 tCO2 / t steel S5: Results output (no process optimization support); Traditional methods only output the carbon emission intensity per ton of steel, and cannot provide carbon flow distribution, sensitivity analysis of key parameters, or optimization suggestions.

[0116] Comparative Example 2 To illustrate the superiority of the proposed method (especially the refined ΔC calculation model) over traditional empirical methods from another perspective, this comparative example demonstrates a ΔC estimation scheme based on a fixed-percentage empirical coefficient that has been or is still in use in some steel enterprises. This scheme simplifies the complex ΔC calculation to a fixed percentage of the total carbon input, completely ignoring the dynamic effects of process parameters and specific loss paths.

[0117] The total carbon input C is considered to be in With total carbon output C out The imbalance ΔC mainly originates from unmeasured dust emissions and measurement system errors. To simplify the calculation, it is assumed that ΔC is related to the total carbon input C. in A fixed proportional relationship is maintained. A fixed empirical coefficient η is typically used to calculate ΔC: ΔC = η × C in η is a fixed loss coefficient that does not change with process conditions such as furnace batch, cold material ratio, temperature, and alkalinity.

[0118] Using the same production data from Example 1, we assume that the traditional experience coefficient η of this factory is 1.5%. Therefore, ΔC = 1.5% × 30.08t = 0.4512t. C in ≈C out +ΔC=29.99+0.4512=30.4412t, Error r = |30.08 - 30.4412| / 30.08 = 1.2% > 1% Using this ΔC value, the direct carbon emission accounting logic remains unchanged, but the final result is indirectly affected by the change in the total carbon output accounting benchmark. The calculated direct carbon emission per ton of steel is 0.0521 tCO2 / t steel (slightly higher than 0.0518 in Example 1), and the carbon emission intensity per ton of steel is 0.1058 tCO2 / t steel.

[0119] This comparative example oversimplifies the calculation of ΔC to a static ratio, fundamentally obscuring the unique and complex nature of the high cold feed ratio smelting process. Not only does its calculation result have a larger equilibrium error, but more importantly, it loses crucial information about the dynamic migration of carbon flow during the process, turning carbon emission assessment into a "black box" estimate and failing to meet the needs of steel companies for refined carbon management and in-depth carbon reduction in processes.

[0120] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features therein. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of this application.

Claims

1. A method for assessing carbon emissions from converter smelting with a high cold charge ratio, characterized in that, include: Collect the mass and carbon content data of all carbon-containing materials during the converter smelting cycle, and calculate the total carbon input C. in ; Collect the mass and carbon / carbon oxide content of all carbon output items during the converter smelting cycle, and calculate the total carbon output C. out ; Based on the principle of conservation of matter, the total carbon input C is established. in With the total carbon output C out The balance model between: C in =C out +ΔC, where ΔC is the model correction parameter; Based on the aforementioned balance model and carbon output tracking data, the direct carbon emissions of the converter steelmaking process are calculated; and combined with the indirect emissions generated by energy consumption, the carbon emission intensity per ton of steel is comprehensively calculated. The calculation of ΔC satisfies the following conditions: ΔC=ΔC real + L d + L g ; ΔC real =ΔC reg +α(T−T target )+β(R−R opt )+γln([CO][CO2]; ΔC reg =k0+k1R c +k2C hot +k3K O2 +ε; L d =λm dust C dust ; L g =μV gas ∑(C CHx ); Where, ΔC real ΔC is a process correction parameter. reg These are the preset model calibration parameters, where T is the molten pool temperature. target The target molten pool temperature is 1600-1680℃; R is the slag basicity. opt The target slag basicity is set at 2.5-4; α, β, and γ are real-time correction coefficients, and L... d For losses due to the escape of extremely fine dust, L g For trace hydrocarbons that were not detected, λ and μ are loss coefficients, where λ ranges from 0.001 to 0.01 and μ ranges from 0.01 to 0.1; m dust For dust quality, C dust V represents the average carbon content of the dust. gas C represents the volume of the flue gas. CHx denoted as , where is the carbon equivalent concentration of various hydrocarbons; k0, k1, k2, and k3 are regression coefficients, determined by least squares fitting; ε is the residual term, with a value less than 0.001; R0 c For cold material ratio, C hot For the carbon content of molten iron, K O2 The oxygen blowing intensity.

2. The carbon emission assessment method for high cold charge ratio smelting in converters according to claim 1, characterized in that, , Let the mass of the i-th carbon-containing raw material be _____. Let be the carbon content of the i-th carbon-containing material. It is the ratio of the relative molecular masses of carbon dioxide to carbon.

3. The carbon emission assessment method for high cold charge ratio smelting in converters according to claim 1, characterized in that, , Let the mass of the i-th carbon-containing solid be physicist. Let m be the carbon content of the i-th carbon-containing solid material. g For the physical mass of carbon-containing gases, This refers to the carbon dioxide content in a carbon-containing gas. The content of carbon monoxide in a carbon-containing gas. This is the ratio of the relative molecular masses of carbon dioxide to carbon monoxide.

4. The carbon emission assessment method for high cold charge ratio smelting in a converter according to claim 1, characterized in that, The direct carbon emissions are The indirect carbon emissions are The carbon emission intensity per ton of steel is E=E direct +E indirect ,in, To capture and utilize carbon dioxide from carbon-containing gases, Let i be the amount of the i-th type of energy medium consumed during the smelting process. is the carbon emission factor of the i-th energy medium consumed during the smelting process.

5. The carbon emission assessment method for high cold charge ratio smelting in a converter according to claim 1, characterized in that, The ΔC also satisfies the following condition: 。 6. The carbon emission assessment method for high cold charge ratio smelting in a converter according to claim 1, characterized in that, The carbon output item includes carbon dust and splashes, and its carbon output is obtained by collecting dust samples for analysis or by using an empirical coefficient method based on material balance.

7. The carbon emission assessment method for high cold charge ratio smelting in a converter according to claim 1, characterized in that, The indirect emissions include indirect carbon emissions generated from the electricity, oxygen, and natural gas consumed during the smelting process.

8. The carbon emission assessment method for high cold charge ratio smelting in a converter according to claim 1, characterized in that, The total carbon input C in and the total carbon output C out The expression is standardized based on the atomic weight converted into equivalent carbon dioxide.

9. The carbon emission assessment method for high cold charge ratio smelting in a converter according to claim 1, characterized in that, Also includes: Based on the carbon emission intensity per ton of steel and the total carbon input C in The total carbon output C out Analyze the impact of key process parameters on carbon emissions; The key process parameters include the cold material ratio, the carbon content of molten iron, the oxygen consumption, and the carbon content of the final molten steel.

10. The carbon emission assessment method for converter high cold charge ratio smelting according to any one of claims 1-9, characterized in that, In the evaluation method, the converter cold charge ratio shall not be less than 20%.

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