Pollution reduction, carbon reduction and technical economy multi-target analysis method and system in lithium metallurgy industry

Abstract

The invention relates to a pollution and carbon reduction and technical economy multi-target analysis method and system in the lithium metallurgy industry, and belongs to the technical field of environment and economy collaborative evaluation in the lithium metallurgy industry. According to the technical scheme, a pollutant and greenhouse gas life cycle accounting model covering a basic production system, an auxiliary production system, an auxiliary production system and a power generation system is constructed, and the emission amount is calculated by adopting an emission factor method and a classification actual measurement method. Meanwhile, a technical economic analysis model is constructed to calculate marginal emission reduction cost of emission reduction measures and form a marginal emission reduction cost curve, then collaborative emission reduction economic indexes brought into a greenhouse gas emission transaction plan and an environment tax mechanism are calculated, and multi-target performance collaborative evaluation is achieved in combination with regulatory factors. And finally, constructing a comprehensive evaluation framework by adopting a modular architecture. The technology can solve the problems of lagging of traditional evaluation data, narrow accounting range and lack of collaborative evaluation, improves the evaluation accuracy and universality, and provides support for pollution and carbon reduction and related decisions in the lithium metallurgy industry.

Description

Technical Field

[0001] This invention belongs to the field of environmental and economic collaborative assessment technology in the lithium metallurgical industry, specifically involving a multi-objective analysis method and system for pollution reduction, carbon reduction, and techno-economic factors in the lithium metallurgical industry. Background Technology

[0002] Lithium metal is a strategic mineral resource widely used in energy storage, metallurgy, chemicals, metal processing, and electronics. Lithium production is a typical energy-intensive and high-emission industry. Currently, the main industrial methods for obtaining lithium include roasting-leaching, brine extraction, and recycling of retired lithium-ion batteries, involving numerous and complex processes. Due to technological limitations and market costs, brine extraction accounts for only a small portion of total lithium production, with more than half relying on roasting-leaching processes. Industrially, the roasting process commonly uses fossil fuel-powered rotary kilns. This process releases large amounts of CO2, SO2, and NO. X Air pollutants such as PM2.5 are prevalent. Throughout the production process, numerous stages involve the co-production and co-emission of greenhouse gases and pollutants, making end-of-pipe treatment equipment insufficient to effectively achieve coordinated pollution reduction and carbon reduction across the entire process. To achieve clean and sustainable development of the lithium industry and related downstream sectors, a green revolution in technology and processes is crucial. Simultaneously, a life-cycle approach is needed to conduct multi-objective performance evaluations of emerging technologies regarding greenhouse gases, pollutants, and emission reduction costs. This will provide important quantitative references for enterprises and policymakers to promote technological innovation within the industry.

[0003] Life cycle assessment and techno-economic analysis have been widely used to assess the environmental impacts of lithium production. These comprehensive assessments provide valuable data resources for the environmental and economic analysis of emerging technologies. The assessment framework includes two main modeling paths: (1) macro-level modeling using existing energy models and public databases, and (2) bottom-up expert models using actual enterprise production data. Both approaches have theoretical and practical limitations. Current life cycle assessment and energy modeling databases face two key limitations: limited availability of validated datasets and significant time lags in dynamic data updates, both of which affect the temporal accuracy of sustainability assessments. Bottom-up expert models have great potential to improve data quality, but their implementation requires significant costs and long assessment times. However, the most pressing limitation is the lack of a systematic approach to achieve synergistic control of pollutant and greenhouse gas emissions in these modeling paradigms. Most research has been conducted at a decentralized, small-scale, and single-media stage, with accounting boundaries limited to air pollutants and CO2, lacking a broader multi-objective synergistic performance assessment method. Summary of the Invention

[0004] To address the aforementioned problems in the existing technology, this invention provides a multi-objective analysis method and system for pollution reduction, carbon reduction, and techno-economic aspects in the lithium metallurgical industry.

[0005] The objective of this invention can be achieved through the following technical solutions: In a first aspect, this invention provides a multi-objective analysis method for pollution reduction and carbon reduction and techno-economic considerations in the lithium metallurgical industry, comprising: A life cycle accounting model for pollutants and greenhouse gases was constructed, the accounting scope was determined, and the emission factor method and classification measurement method were used to calculate the emissions of pollutants and greenhouse gases. Construct a techno-economic analysis model, calculate the marginal emission reduction cost of emission reduction measures based on the calculated emissions, and form a marginal emission reduction cost curve; Calculate the economic index of synergistic emission reduction of pollutants and greenhouse gases, and achieve multi-objective performance synergistic evaluation by harmonizing synergistic emission reduction factors, adjustment factors and signal functions; A modular architecture is used to build a comprehensive evaluation framework for the above analysis methods.

[0006] In a further embodiment of the present invention, the accounting scope includes a basic production system, an auxiliary production system, an ancillary production system, and a power generation system; wherein, the basic production system includes lithium ore pretreatment, roasting, and leaching processes, the auxiliary production system includes conveyor belts, waste gas treatment, wastewater treatment, and solid waste treatment processes, and the ancillary production system includes employee dormitories, canteens, and office buildings.

[0007] In a further embodiment of the present invention, the greenhouse gas includes CO2, and the total CO2 emissions are: , , , , , , , , , Among them, E CO2 E represents the total annual CO2 emissions. CO2-ele Emissions caused by electricity consumption, E CO2-heat Emissions caused by heat energy consumption, E CO2-fuel Emissions caused by fuel consumption, E CO2-process For direct carbon emissions, R CO2For carbon dioxide captured and utilized within the system boundary, AD CO2-m EF is the calorific value. CO2-m As a carbon dioxide emission factor, FC CO2-m For net mass consumption, NCV CO2-m Net calorific value, CC CO2-m Carbon content per unit energy, OF CO2-m For carbon oxidation rate, EF CO2-ele EF is the carbon dioxide emission factor for electricity generation. CO2-heat AD is the carbon dioxide emission factor generated by thermal energy. CO2-raw EF represents the annual consumption of carbonates in raw materials. CO2-raw PUR is the carbon dioxide emission factor for carbonates. raw V represents the mass fraction of carbonate content in the raw materials. heat m is the enthalpy of the process steam. in m is the input mass flow rate of the steam system. out V is the output mass flow rate of the steam system. in V represents the amount of carbon dioxide input into the system. out PUR represents the carbon dioxide output within the system. in PUR represents the purity level of carbon dioxide input into the system. out ρ represents the purity level of the carbon dioxide output from the system. e CO2 This represents the density of carbon dioxide.

[0008] In a further embodiment of the present invention, pollutants are calculated using the emission factor method, the formula of which is: , Among them, E ij Let AO be the actual emission of pollutant j, AO be the annual output of the product, and EF be the actual emission of pollutant j. ij This is the emission factor.

[0009] In a further embodiment of the present invention, pollutants are accounted for using a direct measurement method, the formula of which is: , Among them, E meas For pollutant emissions, Q ij,t,k C represents the mass flow rate of pollutant j within a specified monitoring period t. ij,t,k The concentration of pollutant j within the specified monitoring period t.

[0010] In a further embodiment of the present invention, the specific formula for calculating the marginal emission reduction cost is as follows: , , , , , Among them, MAC ij AI is the marginal emission reduction cost of emission control measure i for pollutant j. i For annualized investment costs, OMC i B represents annual operating and maintenance expenses, and B represents annual economic benefits. i-ext For additional revenue, AR ij For the target annual emission reduction, I i d represents the initial investment cost. i Let ΔELE be the discount rate. i For the reduction of electricity, ΔFUEL i For fuel reduction, ELE prod FUEL cir Potential for energy recovery.

[0011] In a further embodiment of the present invention, the target annual emission reduction includes two parts: pollutant emission reduction and CO2 emission reduction, specifically: , , Where, ΔE i-CO2 For pollutant emission reduction, ΔE ij This refers to CO2 emission reductions.

[0012] In a further embodiment of the present invention, the calculation of the synergistic emission reduction economic index also incorporates greenhouse gas emission trading schemes and environmental tax mechanisms, and the adjustment factor α is determined according to the following conditional function: , Among them, AR ij Stad represents the achievable emission reductions for pollutants. IA E is the standard limit. ij-start Implementing measure i will increase the emissions of pollutant j, E ij-end This represents the actual annual emissions after the emission reduction measures were implemented.

[0013] In a further embodiment of the present invention, the synergistic emission reduction factor is calculated by the cross ratio of emission reduction to emission, specifically: , Among them, co-degree ij As a synergistic emission reduction factor, E j E CO2 For emissions, ΔE ij ΔE i-CO2 To reduce emissions.

[0014] In a second aspect embodiment of the present invention, a multi-objective analysis system for pollution reduction and carbon reduction and techno-economic factors in the lithium metallurgical industry is provided, which utilizes the multi-objective analysis method for pollution reduction and carbon reduction and techno-economic factors in the lithium metallurgical industry provided in a first aspect embodiment of the present invention.

[0015] This invention has at least the following beneficial effects: 1. This invention framework summarizes various process technologies for lithium metal production, and is not limited to a single technology or process, making it applicable to the evaluation of the entire industry.

[0016] 2. A pollutant and greenhouse gas emission accounting model is constructed by combining the emission factor method and the classification measurement method, which avoids the subjective errors caused by a single method.

[0017] 3. Compared with traditional accounting models, the accounting scope is expanded to include waste gas, wastewater, solid waste and various greenhouse gases, and dimensionless processing of high-latitude data is achieved.

[0018] 4. Marginal emission reduction costs are incorporated as one of the components into the comprehensive evaluation indicators, rather than being assessed as separate economic indicators. This avoids interference with the overall priority order caused by separate assessments of environmental and economic aspects. Attached Figure Description

[0019] To facilitate understanding by those skilled in the art, the present invention will be further described below with reference to the accompanying drawings.

[0020] Figure 1 This is a flowchart of a method provided in one embodiment of the present invention; Figure 2 This is a flowchart of the emission factor method for calculating pollutants provided in one embodiment of the present invention; Figure 3 This is a flowchart of the direct measurement method for calculating pollutants provided in one embodiment of the present invention. Detailed Implementation

[0021] To further illustrate the technical means and effects of the present invention in achieving its intended purpose, the following detailed description of the specific implementation methods, structures, features, and effects of the present invention, in conjunction with the accompanying drawings and preferred embodiments, is provided.

[0022] Please refer to Figure 1-3 The present invention provides a multi-objective analysis method for pollution reduction and carbon reduction and techno-economic factors in the lithium metallurgical industry, comprising: A life cycle accounting model for pollutants and greenhouse gases was constructed, the accounting scope was determined, and the emission factor method and classification measurement method were used to calculate the emissions of pollutants and greenhouse gases. Construct a techno-economic analysis model, calculate the marginal emission reduction cost of emission reduction measures based on the calculated emissions, and form a marginal emission reduction cost curve; Calculate the economic index of synergistic emission reduction of pollutants and greenhouse gases, and achieve multi-objective performance synergistic evaluation by harmonizing synergistic emission reduction factors, adjustment factors and signal functions; A modular architecture is used to build a comprehensive evaluation framework for the above analysis methods.

[0023] In this embodiment, the method focuses on full-process accounting, cost analysis, collaborative evaluation, and flexible adaptation. It achieves multi-objective analysis of pollution reduction and carbon reduction and techno-economic aspects in the lithium metallurgical industry through four progressive steps. The implementation process must be carried out around data traceability, method verifiability, and result applicability to ensure that each step matches the actual scenario of lithium production process.

[0024] Specifically, the construction of a life cycle accounting model for pollutants and greenhouse gases first requires defining the accounting boundaries based on relevant environmental protection guidelines, covering the entire lithium production process to avoid omitting key links; secondly, it involves determining the accounting objects, including air pollutants, greenhouse gases, wastewater pollutants, and solid waste; finally, it employs a combination of emission factor method and classification measurement method for accounting: for pollutants with stable emission characteristics and authoritative coefficients, the emission factor method is used; for pollutants whose emissions are greatly affected by operating condition fluctuations and require precise measurement, the classification measurement method is used. The two methods are mutually verified to reduce the subjective error of a single method.

[0025] A techno-economic analysis model is constructed based on the calculated baseline emissions of pollutants and greenhouse gases to determine the emission reduction measures to be evaluated. The core economic parameters of the emission reduction measures are calculated: the annualized investment cost is calculated using the initial investment cost and discount rate, the annual operation and maintenance expenditure is calculated, and the annual economic benefits generated by the emission reduction are calculated. Then, based on the difference in emissions before and after the implementation of the emission reduction measures, the target annual emission reduction is determined. Finally, the marginal emission reduction cost is calculated according to the logic of marginal emission reduction cost = (annualized investment cost + operation and maintenance expenditure - annual economic benefits) / target annual emission reduction, and sorted by emission reduction from small to large or cost from low to high to form a marginal emission reduction cost curve, which intuitively shows the cost-benefit relationship of different emission reduction measures.

[0026] The calculation of the synergistic emission reduction economic index and the achievement of multi-objective performance synergy assessment first involves calculating the synergistic emission reduction factor: based on the obtained pollutant emission reduction, CO2 emission reduction, and calculated baseline emissions, the degree of synergy between emission reduction measures and carbon reduction is reflected through logical calculation of the cross-ratio of the synergistic emission reduction factor. Second, the adjustment factor is determined: based on the relationship between achievable pollutant emission reductions and industry or regional emission standard limits, the adjustment factor is determined through a conditional function to reflect the suitability of emission reduction targets and policy requirements. Then, a signal function is introduced to assess the balance between marginal emission reduction costs and direct emission costs. Finally, the synergistic emission reduction factor, adjustment factor, and signal function are harmonized, and combined with the greenhouse gas emissions trading scheme and environmental tax mechanism, the synergistic emission reduction economic index is calculated to achieve unified quantification of environmental and economic benefits, avoiding interference with overall priority order caused by separate assessments.

[0027] A modular architecture is adopted to build a comprehensive evaluation framework, with the aforementioned life cycle accounting, techno-economic analysis, and collaborative performance evaluation designed as independent functional modules. Each module reserves parameter interfaces and data interaction channels: the life cycle accounting module can adjust the accounting steps and parameters according to lithium production processes; the techno-economic analysis module can update economic parameters such as discount rates and energy prices; the collaborative performance evaluation module can adapt to emission limits and policy mechanisms in different regions; users can choose to enable corresponding modules or adjust module parameters according to specific application needs without reconstructing the overall framework, thus enhancing the versatility and flexibility of the method.

[0028] In a further embodiment of the present invention, the accounting scope includes a basic production system, an auxiliary production system, an auxiliary production system, and a power generation system; wherein, the basic production system includes lithium ore pretreatment, roasting, and leaching processes, the auxiliary production system includes conveyor belts, waste gas treatment, wastewater treatment, and solid waste treatment processes, and the auxiliary production system includes employee dormitories, canteens, and office buildings.

[0029] In this embodiment, it is clearly stated that the scope of accounting must cover the basic production system, auxiliary production system, ancillary production system and power generation system. The implementation process must be based on the entire lithium production process chain, defining the coverage boundaries and core links of each system one by one, so as to avoid the problem of traditional accounting only focusing on core production and omitting auxiliary and ancillary links.

[0030] The core coverage of each system is defined in conjunction with the characteristics of lithium production processes, clarifying the specific scope of each system: Basic Production System: Focuses on the core steps of converting lithium resources into target products, such as lithium ore pretreatment, roasting, leaching, and purification. It must ensure coverage of key conversion steps from raw material input to product output. Auxiliary Production System: Covers links that support basic production, including material transportation, pollutant treatment, and equipment maintenance. It must be linked to the needs of basic production links to avoid omitting supporting facilities serving core production. Subsidiary Production System: Includes non-production links that provide support for production personnel, such as employee dormitories, canteens, office buildings, and medical rooms. Energy consumption, resource consumption, and domestic pollutant emissions for these links must be calculated. Power Generation System: Covers links that provide energy for the entire lithium production process, including indirect energy supply links such as self-owned power plants and purchased electricity. Energy consumption and pollutant emissions for this system must be calculated to avoid errors caused by neglecting emissions from the energy supply side in traditional accounting methods.

[0031] Establishing a data linkage mechanism between systems clarifies the flow of materials and energy between each system and establishes a data traceability chain: for example, the roasting process of the basic production system consumes electricity and heat provided by the power generation system, and its exhaust gas needs to be transported to the exhaust gas treatment process of the auxiliary production system; the wastewater treatment process of the auxiliary production system consumes electricity and reagents, and the resulting sludge needs to be included in the solid waste treatment process; the electricity consumption of the auxiliary production system needs to be included in the total power supply of the power generation system. Through data linkage, it is ensured that the energy consumption, material consumption, and emission data of each system are traceable, non-duplicative, and complete, forming a complete accounting data chain.

[0032] The accounting scope should be dynamically adjusted to adapt to changes in the process. If the lithium production process is adjusted, the accounting scope should be updated accordingly: new process steps should be included in the basic production system, new pollutant treatment equipment should be included in the auxiliary production system, and the ancillary facilities corresponding to new personnel should be included in the auxiliary production system. This will ensure that the accounting scope is always consistent with the actual production scenario and maintain the accuracy and timeliness of the assessment.

[0033] In a further embodiment of the present invention, the greenhouse gas includes CO2, and the total CO2 emissions are: , , , , , , , , , Among them, E CO2 E represents the total annual CO2 emissions. CO2-ele Emissions caused by electricity consumption, E CO2-heat Emissions caused by heat energy consumption, E CO2-fuel Emissions caused by fuel consumption, E CO2-process For direct carbon emissions, R CO2 For carbon dioxide captured and utilized within the system boundary, AD CO2-m EF is the calorific value. CO2-m As a carbon dioxide emission factor, FC CO2-m For net mass consumption, NCV CO2-m Net calorific value, CC CO2-m Carbon content per unit energy, OF CO2-m For carbon oxidation rate, EF CO2-ele EF is the carbon dioxide emission factor for electricity generation. CO2-heat AD is the carbon dioxide emission factor generated by thermal energy. CO2-raw EF represents the annual consumption of carbonates in raw materials. CO2-raw PUR is the carbon dioxide emission factor for carbonates. raw V represents the mass fraction of carbonate content in the raw materials. heat m is the enthalpy of the process steam. in m is the input mass flow rate of the steam system. out V is the output mass flow rate of the steam system. in V represents the amount of carbon dioxide input into the system. out PUR represents the carbon dioxide output within the system. in PUR represents the purity level of carbon dioxide input into the system. out ρ represents the purity level of the carbon dioxide output from the system. e CO2 This represents the density of carbon dioxide.

[0034] In this embodiment, CO2 indirect emissions are calculated, including emissions from electricity consumption, emissions from heat energy consumption, and emissions from fuel consumption. These are calculated using the following methods: Electricity consumption emissions: First, the total electricity consumption of the entire lithium production process is statistically analyzed, including purchased electricity and electricity used by the self-owned power plant. Second, the electricity emission coefficient is obtained. Finally, the emissions are calculated as follows: Electricity consumption emissions = Electricity consumption × Electricity emission coefficient, ensuring the timeliness of the coefficient and the comprehensiveness of the consumption statistics. Heat energy consumption emissions: The total amount of various types of heat energy consumed during the production process is statistically analyzed, including purchased heat and heat supplied by the self-owned boiler. The heat energy emission coefficient is obtained, and combined with the enthalpy of the process steam, the emissions are calculated as follows: Heat energy consumption emissions = Heat energy consumption × Heat energy emission coefficient, reflecting the carbon emissions of the heat energy production process. Fuel consumption and emissions: Statistics on the total amount of fossil fuels directly consumed in production, obtaining the net calorific value, carbon content per unit energy, and carbon oxidation rate of the fuel; first calculate the total calorific value of the fuel according to the formula: fuel calorific value = fuel consumption × net calorific value, and then calculate the emissions according to the formula: fuel consumption and emissions = total calorific value of fuel × carbon content per unit energy × carbon oxidation rate × (44 / 12), to ensure that fuel consumption statistics cover the entire system.

[0035] The calculation of direct CO2 emissions mainly originates from the thermal decomposition of carbonates during lithium production. The calculation method is as follows: First, the annual consumption of carbonates in raw materials is calculated; second, the mass fraction of carbonates in raw materials is analyzed; then, the CO2 emission coefficient of carbonates is obtained; finally, the direct emission is calculated as: direct emission = annual consumption of carbonates × mass fraction of carbonates × CO2 emission coefficient of carbonates, ensuring that the raw material decomposition stage is not missed as a direct emission source.

[0036] The calculation method for CO2 recovery within the system boundary is based on the CO2 that can be captured and utilized during lithium production. The calculation method is as follows: statistically analyze the input and output of CO2 within the system; analyze the purity levels of the input and output CO2; obtain the density of CO2 under standard conditions; calculate the carbon recovery amount as (CO2 input amount × input purity - CO2 output amount × output purity) × CO2 density, ensuring that the recovered CO2 amount is deducted from the total emissions to reflect the benefits of carbon recycling.

[0037] The total CO2 emissions are calculated using the logic that total CO2 emissions = indirect emissions + direct emissions - carbon recovery. Data from each step must be cross-validated to ensure the accuracy and reliability of the calculation results.

[0038] In a further embodiment of the present invention, pollutants are calculated using the emission factor method, the formula of which is: , Among them, E ij Let AO be the actual emission of pollutant j, AO be the annual output of the product, and EF be the actual emission of pollutant j. ij This is the emission factor.

[0039] In this embodiment, determining the accounting object and basic data first involves identifying the types of pollutants that need to be accounted for using the emission factor method. These pollutants must meet the conditions of stable emission characteristics and authoritative emission coefficients. Secondly, the annual output of lithium products within the accounting period is statistically analyzed. Finally, the production links corresponding to the pollutants are identified to ensure that the accounting object and the production link correspond one-to-one.

[0040] The standard for obtaining emission coefficients is based on the "Industrial Source Pollution Discharge Accounting Methods and Coefficients Manual". Emission coefficients that match the lithium production process, pollutant type, and production stage should be consulted. For example, the PM emission coefficient for lithium ore crushing and the heavy metal emission coefficient for leaching should be provided. It is necessary to ensure that the process conditions corresponding to the coefficients are consistent with actual production. If there is no directly matching coefficient in the manual, the coefficients of similar processes verified within the industry should be referenced, and the source and basis for the coefficients should be noted to avoid errors caused by self-estimation of coefficients.

[0041] Pollutant emissions are calculated using the logic of pollutant emissions = annual product output × emission coefficient. If the same pollutant corresponds to multiple production stages, the emissions for each stage are calculated separately and then summed. During the calculation process, the data needs to be validated for reasonableness: for example, the calculation results are compared with the pollutant emission levels of enterprises of similar size in the same industry. If the deviation is large, it is necessary to review whether the output statistics are accurate and whether the coefficient selection is appropriate to ensure that the calculation results are within a reasonable range.

[0042] Establish a coefficient update mechanism to regularly check the "Industrial Source Pollution Discharge Accounting Methods and Coefficients Manual" and the latest coefficients issued by national and local ecological and environmental departments. If the coefficients are adjusted due to process improvements or standard updates, the coefficients used for accounting must be updated simultaneously. If there are significant changes in the enterprise's production process, the matching emission coefficients must be re-queried to ensure that the emission factor method is always adapted to the latest production scenarios and standard requirements.

[0043] In a further embodiment of the present invention, pollutants are accounted for using a direct measurement method, the formula of which is: , Among them, E meas For pollutant emissions, Q ij,t,k C represents the mass flow rate of pollutant j within a specified monitoring period t. ij,t,k The concentration of pollutant j within the specified monitoring period t.

[0044] In this embodiment, determining the monitoring target and monitoring plan first involves identifying the type of pollutant that requires direct measurement, as the emission concentration or flow rate of this type of pollutant is easily affected by fluctuations in production conditions; secondly, a monitoring plan is designed, including determining the monitoring period, monitoring frequency, and monitoring locations.

[0045] When selecting monitoring instruments and equipment, choose those that meet national metrological standards and have passed calibration. For example, monitoring air pollutants requires a flue gas sampler and a gas analyzer, monitoring wastewater pollutants requires a water quality sampler and an ion chromatograph, and monitoring solid waste requires a weighing device. The instruments must meet the monitoring parameter requirements. For example, monitoring low concentrations of VOCs requires a high-sensitivity gas chromatograph-mass spectrometer to ensure that the instrument performance is suitable for the monitoring needs.

[0046] Implement on-site monitoring and data recording. Conduct on-site monitoring according to the monitoring plan: During the designated monitoring period, collect pollutant samples or directly measure parameters on time, and record the production conditions during monitoring; the monitoring parameters include the mass flow rate and concentration of pollutants: the mass flow rate is directly measured by a flow meter or obtained by conversion from volumetric flow rate and gas density, and the concentration is obtained by direct analysis by the instrument; each monitoring requires recording at least 3 sets of parallel data. If the deviation of the parallel data exceeds the allowable range, the monitoring must be repeated to ensure the reliability of the data.

[0047] The total pollutant emissions are calculated using the logic of pollutant emissions = Σ (pollutant mass flow rate for each time period during the monitoring period × pollutant concentration for the corresponding time period). If the monitoring period is only a partial period, the annual emissions need to be estimated based on the matching degree between the production conditions during the monitoring period and the annual production conditions. During the calculation process, abnormal data needs to be screened: outliers caused by instrument failure or sudden changes in operating conditions are removed to ensure that the total data can truly reflect the pollutant emission level under normal production conditions.

[0048] In a further embodiment of the present invention, the specific formula for calculating the marginal emission reduction cost is as follows: , , , , , Among them, MAC ij AI is the marginal emission reduction cost of emission control measure i for pollutant j. i For annualized investment costs, OMC i B represents annual operating and maintenance expenses, and B represents annual economic benefits. i-ext For additional revenue, AR ij For the target annual emission reduction, I i d represents the initial investment cost. i Let ΔELE be the discount rate. i For the reduction of electricity, ΔFUEL i For fuel reduction, ELE prod FUEL cir Potential for energy recovery.

[0049] In this embodiment, the first step is to determine the emission reduction measures to be evaluated and the accounting cycle. Select the emission reduction measures to be implemented in the lithium production process and clarify the accounting cycle; define the coverage of the emission reduction measures.

[0050] Calculating the annualized investment cost involves first determining the initial investment cost of the emission reduction measures; secondly, determining the discount rate; and finally, applying the formula: Annualized Investment Cost = Initial Investment Cost × [Discount Rate × (1 + Discount Rate)] n ] / [(1+discount rate) n The calculation of "-1" ensures that the initial investment is evenly distributed over the accounting period.

[0051] The annual operation and maintenance expenditure is used to calculate the annual operation and maintenance costs of emission reduction measures within the accounting period, including: routine equipment maintenance costs, chemical consumption costs, energy consumption costs, and labor operation costs. Each expenditure is determined based on the equipment operation and maintenance manual, material procurement ledger, and salary payment records to ensure that the costs of the entire process of emission reduction measures are covered.

[0052] The annual economic benefits are calculated as follows: Direct benefits include direct revenue and additional revenue. Direct revenue includes energy savings and resource recovery benefits achieved through emission reduction measures, calculated based on energy procurement prices, resource recovery market prices, and the amount of savings / recovery. Additional revenue includes policy subsidies and environmental cost savings obtained through emission reduction measures, determined based on policy documents and environmental tax payment standards. The annual economic benefits are obtained by summing up the direct and additional revenues.

[0053] The target annual emission reduction and marginal emission reduction cost are calculated by subtracting the baseline emission level before implementation from the emission reduction measures. Finally, the marginal emission reduction cost is calculated as (annualized investment cost + annual operation and maintenance expenditure - annual economic benefit) / target annual emission reduction. If the result is positive, it indicates that the measures require investment to achieve emission reduction; if it is negative, it indicates that the measures can achieve a win-win situation of emission reduction and profit.

[0054] In a further embodiment of the present invention, the target annual emission reduction includes two parts: pollutant emission reduction and CO2 emission reduction, specifically: , , Where, ΔE i-CO2 For pollutant emission reduction, ΔE ij This refers to CO2 emission reductions.

[0055] In this embodiment, the baseline emissions and accounting boundary are determined as the annual emissions of pollutants and CO2 from the entire lithium production process before the implementation of emission reduction measures. These emissions are obtained through life cycle accounting methods to ensure that the accounting boundary and pollutant types of the baseline emissions are completely consistent with the emissions after implementation, thus avoiding errors in emission reduction calculations due to boundary differences. If there is no direct accounting data before implementation, analogous data from enterprises with the same process and scale can be used, and the basis for the analogy and the correction method should be noted.

[0056] After the implementation of emission reduction measures, the annual emissions of pollutants and CO2 should be recalculated using the same accounting method and scope as the baseline emissions. If the emission reduction measures are process optimizations, the emissions of each stage after adjustment should be recalculated using the emission factor method or direct measurement method. If the emission reduction measures are equipment upgrades, new monitoring should be added for the upgraded stages, the emissions of that stage after the upgrade should be calculated, and the total emissions of the entire process should be summarized. The emissions after implementation should be monitored or calculated for at least one complete accounting cycle to ensure that the data is stable and verifiable.

[0057] The target annual emission reductions are calculated by category. CO2 emission reductions are calculated as follows: CO2 emission reduction = CO2 baseline emission - CO2 emission after implementation. If CO2 recovery and utilization are involved, the recovery amount must be included in the deduction item of the emission after implementation to ensure that the CO2 emission reduction reflects the combined effect of actual emission reduction and increased recovery and utilization. Pollutant emission reductions are calculated as follows: Pollutant emission reduction = pollutant baseline emission - emission of that pollutant after implementation. If the same emission reduction measure affects multiple pollutants, the emission reduction for each pollutant must be calculated separately to avoid unclear targets due to mixed calculations. All emission reductions must be labeled with the corresponding pollutant type and accounting period to ensure that the data is traceable and comparable.

[0058] In a further embodiment of the present invention, the calculation of the synergistic emission reduction economic index also incorporates greenhouse gas emissions trading schemes and environmental tax mechanisms, and the adjustment factor α is determined according to the following conditional function: , Among them, AR ij Stad represents the achievable emission reductions for pollutants. IA E is the standard limit. ij-start Implementing measure i will increase the emissions of pollutant j, E ij-end This represents the actual annual emissions after the emission reduction measures were implemented.

[0059] In this embodiment, a greenhouse gas emissions trading scheme and an environmental tax mechanism are incorporated. Greenhouse gas emissions trading parameters are obtained by: querying the carbon emissions trading market rules of the region where the enterprise is located to determine the carbon quota allocation method and carbon trading price; and calculating the carbon quota surplus or deficit before and after the implementation of emission reduction measures. If emissions exceed the quota before implementation, the cost of purchasing additional quotas needs to be calculated; if emissions fall below the quota after implementation, the revenue from selling available quotas needs to be calculated. The carbon trading costs or revenues are included in the annual economic benefit portion of the coordinated emission reduction economic index. Environmental tax parameters are obtained by: determining the tax standards for each pollutant according to the "Environmental Protection Tax Law of the People's Republic of China"; calculating environmental tax expenditures before and after the implementation of emission reduction measures: using the formula Environmental tax expenditure = pollutant emissions × tax standard; and including the environmental tax savings in the annual economic benefit to ensure the index reflects the actual cost changes brought about by the policy.

[0060] The adjustment factor α is determined based on the relationship between the achievable emission reduction of a pollutant and the emission standard limit, using a conditional function: First, obtain the emission standard limit for the pollutant for the industry or region; second, determine the achievable emission reduction of the pollutant; finally, judge according to the conditional function: if the achievable emission reduction is ≥ (standard limit - baseline emission), it indicates that the emission reduction measures can achieve the emission standard, and the adjustment factor α is 1; if the achievable emission reduction is < (standard limit - baseline emission), it indicates that the emission standard has not been met after emission reduction, and the adjustment factor α is achievable emission reduction / (standard limit - baseline emission), reflecting the contribution of the emission reduction measures to the achievement of the standard target; the adjustment factor needs to be calculated separately for each pollutant to ensure that it is adapted to the standard requirements of different pollutants.

[0061] The harmonic parameter calculation of the coordinated emission reduction economic index combines the coordinated emission reduction factor, the adjustment factor in this embodiment, and the signal function. The coordinated emission reduction economic index is calculated according to the logic of coordinated emission reduction factor × adjustment factor × signal function × (1 + policy benefit coefficient) (the policy benefit coefficient reflects the proportion of benefits brought by carbon trading and environmental tax). The larger the final index value, the better the synergistic effect of emission reduction measures and the higher the policy adaptability.

[0062] In a further embodiment of the present invention, the synergistic emission reduction factor is calculated by the cross ratio of emission reduction to emission, specifically: , Among them, co-degree ij As a synergistic emission reduction factor, E j E CO2 For emissions, ΔE ij ΔE i-CO2 To reduce emissions.

[0063] In this embodiment, the basic data is obtained from the life cycle accounting module: the baseline emissions of each type of pollutant and the baseline emissions of CO2; and from the emission reduction calculation: the target annual emission reduction of the corresponding pollutant and the target annual emission reduction of CO2; ensuring that the data all correspond to the same accounting period and the same production process to avoid inconsistencies in data caliber.

[0064] The synergistic ratio between a single pollutant and CO2 is calculated for each pollutant using the formula: Synergistic Ratio = (Pollutant Emission Reduction / Baseline Emission of the Pollutant) × (CO2 Emission Reduction / Baseline CO2 Emission). For example, the synergistic ratio between SO2 and CO2 reflects the degree of correlation between SO2 and CO2 emission reductions. If an emission reduction measure significantly reduces both SO2 and CO2 emissions simultaneously, the ratio will be higher; if the measure only reduces a single pollutant, the ratio will be lower. The synergistic ratio between each pollutant and CO2 needs to be calculated separately to reflect the synergistic characteristics of different pollutants.

[0065] The comprehensive synergistic emission reduction factor is determined by weighting the environmental impact of each pollutant in the lithium production process (e.g., by determining the weights based on the tax rates of each pollutant in the Environmental Protection Tax Law or the environmental impact potential of each pollutant in the IPCC guidelines). The synergistic ratio of each pollutant with CO2 is weighted and averaged to obtain the comprehensive synergistic emission reduction factor. The higher the weight of a pollutant, the greater the impact of its synergistic ratio on the comprehensive factor. For example, if CO2 and SO2 are the main emissions from lithium production, their weights are high, and their synergistic ratio dominates the value of the comprehensive factor. The synergistic emission reduction factor ranges from 0 to 1; the closer the value is to 1, the better the synergistic effect of the emission reduction measures on pollution reduction and carbon reduction.

[0066] In some embodiments, the present invention also provides a multi-objective analysis method for pollution reduction and carbon reduction and techno-economic factors in the lithium metallurgical industry, specifically: This method has developed a comprehensive LCA-TEA assessment framework specifically for the lithium industry. The proposed framework comprises three core components: (1) life cycle accounting for pollutants and greenhouse gases; (2) techno-economic analysis and marginal cost-of-reduction (MACC) curve; and (3) co-economic indicators for the joint control of pollutants and greenhouse gases. ij The structure of the LCA-TEA model is shown in the figure.

[0067] The first step is the life cycle accounting of pollutants and greenhouse gases. This part forms the foundation and logical starting point of the entire model framework. The accounting method follows the guidelines established by the Intergovernmental Panel on Climate Change (IPCC) and the National Development and Reform Commission (NDRC) of China. The scope of the accounting is generally divided into three parts: (1) basic production systems, such as lithium ore pretreatment, roasting and leaching; (2) auxiliary production systems, such as conveyor belts, waste gas, wastewater and solid waste treatment; and (3) ancillary production systems, such as staff dormitories, canteens and office buildings. It is advocated to expand the scope of conventional systems in life cycle accounting practice to include power generation systems and other processes that are often excluded but are crucial. Oversimplified accounting methods will inevitably lead to significant errors, thus affecting the reliability of the results.

[0068] The main greenhouse gas produced during lithium production is CO2, and comprehensive carbon emission accounting follows the following approach.

[0069] (1), The annual total CO2 emissions (ECO2) are calculated as follows: indirect emissions (including electricity emissions (ECO2)). CO2-ele ), heat emissions (E) CO2-heat ) and fuel consumption emissions (E CO2-fuel The sum of these, plus the direct carbon emissions that may occur during the decomposition of lithium ore (E) CO2-process ), then subtract the carbon dioxide captured and utilized within the system boundary (R CO2 ).

[0070] Indirect emissions from fossil fuels, heat, and non-renewable energy electricity consumption are the main sources of carbon emissions in lithium production. The quantification method is the emission factor method, as shown in formulas (2)-(4) and (5)-(7), respectively.

[0071] (2), (3), (4), The calorific value (ADCO2-m) is a criterion for measuring all types of energy consumption, and its definition is shown in Formula 3. The fuel-specific carbon dioxide emission factor (tCO2 / GJ, unit: tons of carbon dioxide / gigajoules) depends on the inherent characteristics of the fuel and is calculated through net mass consumption (FCCO2-m, kg or standard cubic meters), net calorific value (NCVCO2-m, kJ / kg, kJ / standard cubic meter), carbon content per unit energy (CCCO2-m, tons of carbon dioxide / gigajoules), and carbon oxidation rate (OFCO2-m, %), where the 44 / 12 coefficient converts the atomic mass of carbon to the molecular mass of carbon dioxide.

[0072] (5), (6), (7), EF CO2-ele and EF CO2-heat These represent the carbon dioxide emission coefficients from electricity and heat energy, respectively, determined based on the latest official data from the relevant national authorities. Furthermore, Equation 7 indicates the enthalpy (V) of the process steam. heat The value (in gigajoules / ton) is thermodynamically dependent on its temperature and pressure conditions. The variable m in and m out These represent the input and output mass flow rates of the steam system, respectively.

[0073] Direct carbon dioxide emissions during lithium extraction primarily originate from the thermal decomposition of lithium carbonate (Li₂CO₃) and other associated carbonates in the raw ore. These emissions can be quantified through stoichiometric analysis of the carbonate carbon content, as shown in Equation 8.

[0074] (8), Among them, AD CO2-raw EF represents the annual consumption (tons / year) of carbonates in raw materials. CO2-raw This represents the carbonate CO2 emission factor (tons of CO2 / tons of carbonate) as defined in the 2019 IPCC Revised Guidelines, where the Li2CO3 emission factor is 0.5955 tons of CO2 per ton. Parameter PUR raw This indicates the mass fraction (%) of carbonate content in the raw materials. Carbon dioxide emitted during lithium production has the potential to be captured and utilized in supercritical carbon dioxide extraction systems, providing an opportunity for carbon recycling. The formula is as follows: (9), The amount of carbon dioxide input (V) in the system in (Nm³) and output (V) out The purity levels (PUR) of each element (Nm³) were quantified and their respective purity levels (PUR) were determined simultaneously. in (, %) and carbon dioxide density (ρ) e CO2 These data (tCO2 / Nm³) are based on standard temperature and pressure conditions (273.15 K, 101.325 kPa).

[0075] The accounting of pollutant emissions is mainly based on two methods: the emission factor method as shown in Formula 10, and the direct measurement method as shown in Formula 11.

[0076] (10), (11), Where AO represents the annual output of the accounting enterprise's products, and EF ij This represents the emission coefficient obtained from the "Handbook of Industrial Source Pollution Discharge Accounting Methods and Coefficients". For direct measurement of pollutants in measure i by device k, specialized instruments are required to simultaneously measure the mass flow rate (Q) of pollutant j within the specified monitoring period t. ij (t,k) and concentration (C) ij ,t,k).

[0077] All pollutant data were standardized through equivalent conversion to comprehensively assess the emission reduction effectiveness of the technology across multiple pollutants. Pollutant Equivalence Index (Ep) j The calculation method for ) is as follows: (12), (13), (14), Where E ij EFp represents the actual emission of pollutant j. j (0≤EFp) j ≤1) represents from valve j The derived environmental impact weighting coefficients. The environmental protection tax for pollutant j is determined in accordance with the "Environmental Protection Tax Law of the People's Republic of China". Within a given tax range, EFp is determined using the median value from Formula 14 through Formula 13. j This is to ensure that the quantification of the relative impact of pollutants remains consistent.

[0078] The second part is the techno-economic analysis. This section uses a marginal cost reduction model to measure the cost-effectiveness of emission reduction technologies at an industrial scale. The basic idea is shown in Equation 15: (15), Marginal emission reduction cost (MAC) of emission control measure i for pollutant j ij AI is defined as the ratio of net implementation cost to emissions reduction. i OMC represents the annualized investment cost calculated using Formula 16. i Including annual operating and maintenance expenses, AR ij B represents the target annual emission reduction calculated using formulas 17-18, while B represents the annual economic benefit calculated using formula 19.

[0079] AR ij It can be divided into pollutant emission reduction (ΔE) i-CO2 ) and CO2 emission reduction (ΔE) ijThe calculation process is similar for both cases, including calculating the difference in emissions of pollutant j from equipment k before and after the implementation of emission reduction measure i.

[0080] (16), (17), (18), (19), Initial investment cost (I i The economic benefits (B) of emission reduction measures are calculated using the discount rate (di) guided by the National Development and Reform Commission of China. For measures lacking clear industry classification, the discount rate is set at 8%. i Equation 20) and fuel reduction (ΔFUEL) i (Equation 21), its value is based on the local market price during the study period (P). ele P fuel ) calculation. Certain technologies may generate additional benefits (B) i-ext Furthermore, energy recovery potential (ELE) must also be considered in comprehensive energy saving calculations. prod FUEL cir ).

[0081] (20), (twenty one), The core of the comprehensive framework is multi-objective performance collaborative analysis, which requires normalization of high-dimensional datasets through the following steps.

[0082] Co-econ ij The calculation process for the co-degree is shown in equation (22). Among them, the co-degree factor... ij ) is achieved through emission reduction (ΔE) ij ΔE i-CO2 ) and emissions (E j E CO2 The cross ratio is calculated as shown in Formula 23.

[0083] (twenty two), (twenty three), (twenty four), Equation (24) embodies the mathematical definition of a conditional function, and is related to the achievable emission reduction (AR) of pollutants. ij ) and standard limits (stad)IA This relates to [the previous sentence]. IA represents the upper limit threshold, which policymakers can adjust based on specific operational constraints and policy requirements. Furthermore, the integrated decision-making framework incorporates market-based environmental policy tools, including greenhouse gas (GHG) emissions trading schemes and environmental tax mechanisms, explicitly stated in Equations 14, 25, and 26. The adjustment factor α is used to adjust the emissions reduction target (AR). ij While considering emission quota limitations, AR ij A negative value means that implementing measure i will increase the emissions of pollutant j. Baseline emissions (E) ij-start E represents the annual emissions of pollutant j before the implementation of measure i, while the treated emissions (E) represent the annual emissions of pollutant j before the implementation of measure i. ij-end This reflects the actual annual emissions after the application of emission reduction measures.

[0084] (25), (26), The signal function (25) will evaluate the emission reduction benefits (MAC). ij ) and direct emissions costs (valve) j The balance between ( ) and ( ). For greenhouse gases, valve j-GHG It is calculated dynamically based on the real-time carbon trading market and the amount of carbon dioxide (TP) traded during the accounting period. CO2 ) and transaction price (tran) CO2 The greenhouse effect coefficients are calculated by multiplying CO2, N2O, and CH4. The greenhouse effect coefficients are 1 for CO2, 274 for N2O, and 79.7 for CH4, and these values ​​are determined according to the greenhouse gas accounting guidelines specified by the Intergovernmental Panel on Climate Change (IPCC). In the final priority ranking stage, the normalized indicators should be transformed into the dataset using Equation (26) to improve readability.

[0085] In a second aspect embodiment of the present invention, a multi-objective analysis system for pollution reduction and carbon reduction and techno-economic factors in the lithium metallurgical industry is provided, which utilizes the multi-objective analysis method for pollution reduction and carbon reduction and techno-economic factors in the lithium metallurgical industry provided in a first aspect embodiment of the present invention.

[0086] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention in any way. Although the present invention has been disclosed above with reference to preferred embodiments, it is not intended to limit the present invention. Any person skilled in the art can make some modifications or alterations to the above-disclosed technical content to create equivalent embodiments without departing from the scope of the present invention. Any simple modifications, equivalent changes and alterations made to the above embodiments based on the technical essence of the present invention without departing from the scope of the present invention shall still fall within the scope of the present invention.

Claims

1. A multi-objective analysis method for pollution reduction and carbon reduction and techno-economic factors in the lithium metallurgical industry, characterized in that, include: A life cycle accounting model for pollutants and greenhouse gases was constructed, the accounting scope was determined, and the emission factor method and classification measurement method were used to calculate the emissions of pollutants and greenhouse gases. Construct a techno-economic analysis model, calculate the marginal emission reduction cost of emission reduction measures based on the calculated emissions, and form a marginal emission reduction cost curve; Calculate the economic index of synergistic emission reduction of pollutants and greenhouse gases, and achieve multi-objective performance synergistic evaluation by harmonizing synergistic emission reduction factors, adjustment factors and signal functions; A modular architecture is used to build a comprehensive evaluation framework for the above analysis methods.

2. The multi-objective analysis method for pollution reduction and carbon reduction and techno-economic factors in the lithium metallurgical industry according to claim 1, characterized in that, The accounting scope includes the basic production system, auxiliary production system, subsidiary production system, and power generation system; the basic production system includes lithium ore pretreatment, roasting, and leaching processes; the auxiliary production system includes conveyor belts, waste gas treatment, wastewater treatment, and solid waste treatment processes; and the subsidiary production system includes employee dormitories, canteens, and office buildings.

3. The multi-objective analysis method for pollution reduction and carbon reduction and techno-economic factors in the lithium metallurgical industry according to claim 1, characterized in that, The greenhouse gas includes CO2, and the total CO2 emissions are: ， ， ， ， ， ， ， ， ， Among them, E CO2 E represents the total annual CO2 emissions. CO2-ele Emissions caused by electricity consumption, E CO2-heat Emissions caused by heat energy consumption, E CO2-fuel Emissions caused by fuel consumption, E CO2-process For direct carbon emissions, R CO2 For carbon dioxide captured and utilized within the system boundary, AD CO2-m EF is the calorific value. CO2-m As a carbon dioxide emission factor, FC CO2-m For net mass consumption, NCV CO2-m Net calorific value, CC CO2-m Carbon content per unit energy, OF CO2-m For carbon oxidation rate, EF CO2-ele EF is the carbon dioxide emission factor for electricity generation. CO2-heat AD is the carbon dioxide emission factor generated by thermal energy. CO2-raw EF represents the annual consumption of carbonates in raw materials. CO2-raw PUR is the carbon dioxide emission factor for carbonates. raw V represents the mass fraction of carbonate content in the raw materials. heat m is the enthalpy of the process steam. in m is the input mass flow rate of the steam system. out V is the output mass flow rate of the steam system. in V represents the amount of carbon dioxide input into the system. out PUR represents the carbon dioxide output within the system. in PUR represents the purity level of carbon dioxide input into the system. out ρ represents the purity level of the carbon dioxide output from the system. e CO2 This represents the density of carbon dioxide.

4. The multi-objective analysis method for pollution reduction and carbon reduction and techno-economic factors in the lithium metallurgical industry according to claim 1, characterized in that, The formula for calculating pollutants using the emission factor method is as follows: ， Among them, E ij Let AO be the actual emission of pollutant j, AO be the annual output of the product, and EF be the actual emission of pollutant j. ij This is the emission factor.

5. The multi-objective analysis method for pollution reduction and carbon reduction and techno-economic factors in the lithium metallurgical industry according to claim 1, characterized in that, The formula for calculating pollutants using the direct measurement method is as follows: ， Among them, E meas For pollutant emissions, Q ij,t,k C represents the mass flow rate of pollutant j within a specified monitoring period t. ij,t,k The concentration of pollutant j within the specified monitoring period t.

6. The multi-objective analysis method for pollution reduction and carbon reduction and techno-economic factors in the lithium metallurgical industry according to claim 1, characterized in that, The specific formula for calculating the marginal emission reduction cost is as follows: ， ， ， ， ， Among them, MAC ij AI is the marginal emission reduction cost of emission control measure i for pollutant j. i For annualized investment costs, OMC i B represents annual operating and maintenance expenses, and B represents annual economic benefits. i-ext For additional revenue, AR ij For the target annual emission reduction, I i d represents the initial investment cost. i Let ΔELE be the discount rate. i For the reduction of electricity, ΔFUEL i For fuel reduction, ELE prod FUEL cir Potential for energy recovery.

7. The multi-objective analysis method for pollution reduction and carbon reduction and techno-economic factors in the lithium metallurgical industry according to claim 6, characterized in that, The target annual emission reduction includes two parts: pollutant emission reduction and CO2 emission reduction, specifically: ， ， Where, ΔE i-CO2 For pollutant emission reduction, ΔE ij This refers to CO2 emission reductions.

8. The multi-objective analysis method for pollution reduction and carbon reduction and techno-economic factors in the lithium metallurgical industry according to claim 1, characterized in that, The calculation of the synergistic emission reduction economic index also incorporates greenhouse gas emissions trading schemes and environmental tax mechanisms, and the adjustment factor α is determined according to the following conditional function: ， Among them, AR ij Stad represents the achievable emission reductions for pollutants. IA E is the standard limit. ij-start Implementing measure i will increase the emissions of pollutant j, E ij-end This represents the actual annual emissions after the emission reduction measures were implemented.

9. The multi-objective analysis method for pollution reduction and carbon reduction and techno-economic factors in the lithium metallurgical industry according to claim 1, characterized in that, The synergistic emission reduction factor is calculated using the cross ratio of emission reductions to emissions, specifically: ， Among them, co-degree ij As a synergistic emission reduction factor, E j E CO2 For emissions, ΔE ij ΔE i-CO2 To reduce emissions.

10. A multi-objective analysis system for pollution reduction and carbon reduction and techno-economic factors in the lithium metallurgical industry, characterized in that, The method for multi-objective analysis of pollution reduction, carbon reduction, and techno-economic factors in the lithium metallurgical industry, as described in any one of claims 1-9.

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