A blockchain state witness-based industrial flue gas treatment system carbon footprint accounting and low-carbon performance verification method and system

Abstract

The application discloses a kind of industrial flue gas treatment system carbon footprint accounting and low carbon performance verification method and system based on block chain state witness, relating to industrial production process carbon footprint accounting, credible data traceability and low carbon performance verification technology.It divides target production line running time into accounting window, collects product yield data and including activity data, environmental protection standard data, measurement state data, working condition state data governance operation data;Calculate carbon emissions and unit product flue gas treatment carbon footprint, determine emission compliance state, data quality grade and working condition category;When there are two or more working condition categories in the same accounting window, it is divided into sub-accounting window;State witness is generated and written into block chain;Based on the effective accounting window verified by integrity, evaluation object is calculated, and compared with the benchmark unit product flue gas treatment carbon footprint to generate low carbon performance verification result.The system includes edge collection node, processor, memory and block chain interaction node.

Description

Technical Field

[0001] The present invention relates to data processing technologies for management, supervision and evaluation purposes, in particular to carbon footprint accounting, trusted data traceability and low-carbon performance verification technologies for industrial production processes, and specifically relates to a method and system for carbon footprint accounting and low-carbon performance verification of industrial flue gas treatment systems based on blockchain state witnessing. Background Art

[0002] With the increasing demand for product carbon footprint assessment, carbon label certification, green supply chain management and low-carbon performance verification, industrial enterprises have an increasing need to account for, record and verify carbon emissions in the production process. For industrial production scenarios such as iron and steel, cement, chemical industry, building materials and non-ferrous metal smelting, flue gas treatment systems for desulfurization, denitration, dust removal, adsorption, waste heat recovery and the like usually operate as environmental protection treatment facilities supporting production lines. During the operation process, the flue gas treatment system will consume energy, materials or consumables such as electric power, steam, compressed air, desulfurizers, denitration agents, adsorbents, catalysts and filter bags, and may also involve matters such as by-product disposal, waste disposal and waste heat recovery. Therefore, the flue gas treatment system itself will also generate a certain amount of carbon emissions or carbon emission deductions, and affect the carbon footprint per unit of industrial products.

[0003] A variety of carbon footprint accounting and management schemes have been proposed in the prior art. For example, the patent application with publication number CN114662781A discloses a cloud-based intelligent carbon footprint assessment management system and its assessment method, which realizes carbon footprint calculation, report generation, data visualization and uncertainty analysis through a cloud platform. The patent application with publication number CN114358668A discloses a carbon footprint big data analysis method and system based on industrial Internet identifiers, which uses industrial Internet identifiers to collect and associate product life cycle information so as to realize traceability and analysis of carbon footprint data. The patent application with publication number CN108226390A discloses a blockchain carbon emission monitoring device and monitoring system, which combines carbon emission monitoring data with blockchain technology to improve the credibility of carbon emission data.

[0004] However, the above-mentioned prior art is mainly oriented to the overall carbon emission of enterprises, the carbon footprint of the whole product life cycle or the deposit and management of carbon emission data, and it is still difficult to finely characterize the contribution of the industrial flue gas treatment system to the carbon footprint per unit of the target product under different operating states. In the actual industrial site, the operation of the flue gas treatment system will be affected by factors such as production line load, pollutant generation level, operation status of treatment equipment, maintenance status, metering equipment status and environmental protection monitoring status. If the consumption of energy, chemicals or consumables of the flue gas treatment system is only summarized according to a fixed statistical period and then directly allocated to the product output, the data under different operating states may be mixed for evaluation, thus affecting the accuracy and comparability of the carbon footprint accounting result per unit product.

[0005] Meanwhile, data related to flue gas treatment systems typically originates from multiple data sources, including production management systems, distributed control systems, continuous emission monitoring systems, and equipment operation logs. These different data sources vary in terms of time resolution, data integrity, data source reliability, calibration or verification status of metering equipment, manual data entry, and outlier handling. Without effective constraints and verification of the reliability of on-site data, carbon footprint accounting results may fail to meet the requirements of subsequent audits, certifications, performance evaluations, or third-party verifications.

[0006] Furthermore, low-carbon retrofitting, operational optimization, or contractual energy conservation and carbon reduction services typically require comparisons of carbon footprint levels before and after the retrofit, during different operational periods, or between different evaluation targets. If the status, source, and accounting basis of the basic data lack verifiable records, or if the carbon footprint results are only preserved in the form of a final report, it will be difficult to reliably verify the low-carbon performance results subsequently, affecting the use of the verification results in project acceptance, operational evaluation, or third-party verification. Summary of the Invention

[0007] The purpose of this invention is to provide a method and system for carbon footprint accounting and low-carbon performance verification of industrial flue gas treatment systems based on blockchain state witnessing, which solves the problem that existing carbon footprint accounting methods are difficult to accurately, reliably and verifiably characterize the carbon emission contribution of flue gas treatment systems at the unit product level of the target production line, resulting in insufficient evidence for low-carbon performance verification.

[0008] Firstly, a method for carbon footprint accounting and low-carbon performance verification of an industrial flue gas treatment system based on blockchain-based state witnessing is provided, comprising: S1, dividing the operating time of the target production line into multiple accounting windows; S2, within each accounting window, collecting product output data of the target production line and treatment operation data of the flue gas treatment system, wherein the treatment operation data includes activity data for calculating carbon emissions, environmental compliance data for determining whether pollutants are discharged in compliance with standards, metering status data for determining the reliability of the data, and operating condition status data for determining the operating condition category of the accounting window; S3, calculating the carbon emissions of the flue gas treatment system within the accounting window based on the activity data and the carbon emission factor corresponding to the activity data. S4. When the product output within the accounting window is greater than zero, divide the carbon emissions of the flue gas treatment system within the accounting window by the product output within the accounting window to obtain the unit product flue gas treatment carbon footprint within the accounting window; S5. Determine the emission compliance status of the accounting window based on the environmental compliance data, determine the data quality level of the accounting window based on the metering status data, and determine the operating condition category of the accounting window based on the operating condition status data; S6. Based on the product output data, treatment operation data, emission compliance status, data quality level, operating condition category, accounting model version, and accounting rule version within the accounting window, generate a status witness to prove that the data and status of the accounting window have not been tampered with, and write the status witness into the blockchain; S7. S8. Obtain status witnesses for multiple accounting windows corresponding to the evaluation object, perform integrity verification on the status witnesses, and filter out valid accounting windows from the multiple accounting windows based on the product output data, emission compliance status, data quality level, and operating condition category corresponding to the status witnesses that have passed integrity verification. The valid accounting window is an accounting window where the product output is greater than zero, the emission compliance status is compliant, the data quality level meets the preset requirements, the operating condition category belongs to the preset valid operating condition category, and the data and status have passed integrity verification; S9. Divide the total carbon emissions of the flue gas treatment system in the valid accounting window by the total product output in the valid accounting window to obtain the unit product flue gas treatment carbon footprint of the evaluation object; S10. Obtain the benchmark unit product flue gas treatment carbon footprint corresponding to the benchmark object, and generate low-carbon performance verification results based on the comparison results between the unit product flue gas treatment carbon footprint of the evaluation object and the benchmark unit product flue gas treatment carbon footprint.

[0009] Furthermore, the activity data includes resource consumption data characterizing the carbon emissions generated by the flue gas treatment system within the accounting window, and, when there are recycling deductions, recycling deduction data characterizing the carbon emission deduction status; the environmental compliance data includes measured pollutant emission data characterizing the actual pollutant emission level within the accounting window, and pollutant emission limit data used to determine the pollutant compliance judgment benchmark; the metering status data includes data source status data characterizing the reliability of the data source, calibration or verification status data characterizing whether the metering equipment has been calibrated or verified, and data integrity and abnormal status data characterizing whether the data is complete or abnormal; the operating condition data includes equipment commissioning status data used to determine whether the flue gas treatment system is put into operation along with the target production line, and operating condition data used to determine whether the flue gas treatment system meets the preset operating conditions, the operating condition data including operating mode data, operating load data, and key operating parameter data.

[0010] Furthermore, the carbon emissions of the flue gas treatment system within this accounting window are calculated using the following formula: E(T)=ΣA i (T)×EF i , i = 1, 2, ..., n; where T represents the accounting window, E(T) represents the carbon emissions of the flue gas treatment system within the accounting window T, and A i (T) represents the i-th type of activity data within the accounting window T, EF i Σ represents the carbon emission factor corresponding to the i-th type of activity data, n represents the number of types of activity data, and Σ represents the summation of all types of activity data i = 1, 2, ..., n. When the i-th type of activity data is recycling deduction data, the corresponding carbon emission factor is negative or deducted according to the preset deduction rules.

[0011] Furthermore, the carbon footprint of flue gas treatment per unit product within the accounting window is calculated according to the following formula: I(T)=E(T) / Q(T); where I(T) represents the carbon footprint of flue gas treatment per unit product within the accounting window T, E(T) represents the carbon emissions of the flue gas treatment system within the accounting window T, Q(T) represents the product output within the accounting window T, and Q(T)>0.

[0012] Furthermore, generating the status witness includes: performing hash digest processing on the product output data and governance operation data within the accounting window to obtain a data evidence digest; performing hash digest processing on the emission compliance status, data quality level, operating condition category, accounting model version, and accounting rule version of the accounting window to obtain a status digest; and generating the status witness based on the data evidence digest, status digest, accounting window identifier, target production line identifier, and edge acquisition node signature; wherein the status witness is associated with the product output data, governance operation data, emission compliance status, data quality level, and operating condition category of the accounting window.

[0013] Furthermore, after obtaining the status witnesses of multiple accounting windows corresponding to the evaluation object, the product output data, governance operation data, emission compliance status, data quality level, and operating condition category corresponding to the status witness are read according to the accounting window identifier; the status witness to be verified is regenerated according to the hash digest processing rules used when generating the status witness; the status witness to be verified is compared with the status witness written to the blockchain for consistency; when the status witness to be verified is consistent with the status witness written to the blockchain, it is determined that the data and status of the accounting window have passed the integrity verification, and the accounting window is allowed to participate in the selection of valid accounting windows; when the status witness to be verified is inconsistent with the status witness written to the blockchain, it is determined that the data and status of the accounting window have not passed the integrity verification, and the accounting window is prohibited from participating in the selection of valid accounting windows.

[0014] Furthermore, the operating condition categories include effective operating conditions and ineffective operating conditions. Effective operating conditions refer to the operating conditions where the flue gas treatment system is put into operation with the target production line and meets preset operating conditions. Ineffective operating conditions refer to the operating conditions where the flue gas treatment system is not put into operation with the target production line or does not meet the preset operating conditions. The preset effective operating condition categories include the effective operating conditions. When there are two or more operating condition categories within the same accounting window, the accounting window is divided into two or more sub-accounting windows based on the time point when the operating condition category changes. According to the start and end times of each sub-accounting window, the product output data, treatment operation data, and other data for each sub-accounting window are determined respectively. The system calculates the carbon emissions of the flue gas treatment system within each sub-accounting window, based on emission compliance status, data quality level, and operating condition category, and generates corresponding status witnesses. The effective accounting window selection uses the sub-accounting window as the selection object, the evaluation object aggregation calculation is based on the selected sub-accounting windows, and the low-carbon performance verification is based on the results of the evaluation object aggregation calculation. When the operating condition category of an accounting window or sub-accounting window belongs to the ineffective operating condition category, the accounting window or sub-accounting window is marked as an ineffective accounting window, or the carbon emissions of the flue gas treatment system within the accounting window or sub-accounting window are aggregated into ineffective operating condition carbon emissions.

[0015] Furthermore, the benchmark objects are historical operating periods, initial commissioning benchmark periods, design guarantee values, contractual target values, industry benchmark values, benchmark values ​​of similar devices, or operating periods before modification; the evaluation objects are current operating cycles, commissioning assessment periods, operation and maintenance service periods, low-carbon optimized operating periods, contract acceptance periods, monthly accounting periods, quarterly accounting periods, annual accounting periods, or operating periods after modification.

[0016] Furthermore, assuming the effective accounting window set is Ω, the unit product flue gas treatment carbon footprint of the evaluated object is calculated according to the following formula: I e =ΣE(T) / ΣQ(T), T∈Ω; where I e Let Ω represent the carbon footprint of flue gas treatment per unit product of the evaluated object, Σ represent the set of effective accounting windows, Σ represent the summation of all effective accounting windows within the set Ω, T represent a single effective accounting window within the set Ω, E(T) represent the carbon emissions of the flue gas treatment system within the effective accounting window T, and Q(T) represent the product output within the effective accounting window T. The low-carbon performance verification result is determined based on the reduction rate of low-carbon performance, which is calculated according to η = (I b -I e ) / I b Calculated by multiplying by 100%, where η represents the reduction in low-carbon performance, and I b The carbon footprint of flue gas treatment per unit of benchmark product is represented; when the reduction in low-carbon performance reaches the preset low-carbon performance threshold, and the number or proportion of the effective accounting windows meets the preset window requirements, a low-carbon performance verification result is generated.

[0017] Secondly, a system for carbon footprint accounting and low-carbon performance verification of an industrial flue gas treatment system based on blockchain state witnessing is provided, including an edge acquisition node, a blockchain interaction node, a processor, and a memory. The edge acquisition node is used to collect product output data of the target production line and treatment operation data of the flue gas treatment system. The blockchain interaction node is used to write state witnesses to the blockchain and obtain state witnesses of multiple accounting windows corresponding to the evaluation object from the blockchain. The memory stores a computer program. When the processor executes the computer program, it causes the system to execute the method for carbon footprint accounting and low-carbon performance verification of an industrial flue gas treatment system based on blockchain state witnessing described in the first aspect.

[0018] This invention divides the operating time of the target production line into multiple accounting windows, and collects product output data and flue gas treatment system operation data in each accounting window. This allows the carbon emissions of the flue gas treatment system to correspond to the product output of the target production line in the corresponding accounting window. This avoids the problem of mixed evaluation of different operating status data caused by simply summarizing consumption according to a fixed statistical period and directly allocating it to product output. As a result, it helps to improve the accuracy and comparability of the carbon footprint accounting results of flue gas treatment per unit product.

[0019] The governance operation data of this invention includes activity data, environmental compliance data, metering status data, and operating condition data. Activity data is used to calculate the carbon emissions of the flue gas treatment system within the accounting window; environmental compliance data is used to determine the emission compliance status; metering status data is used to determine the data quality level; and operating condition data is used to determine the operating condition category. Therefore, this invention not only considers the resource consumption and recycling deduction of the flue gas treatment system, but also incorporates whether pollutant emissions meet standards, the reliability of the data, and the operating condition of the flue gas treatment system into the carbon footprint accounting and evaluation process, enabling the carbon footprint of flue gas treatment per unit product to more accurately reflect the carbon emission contribution of the flue gas treatment system under effective operating conditions.

[0020] This invention selects effective accounting windows from multiple accounting windows corresponding to the evaluation object based on product output data, emission compliance status, data quality level, and operating condition category. The total carbon emissions of the flue gas treatment system within each effective accounting window are divided by the total product output within that window to obtain the unit product flue gas treatment carbon footprint of the evaluation object. This method reduces the impact of accounting windows with zero product output, non-compliance with emissions standards, unsatisfactory data quality, or operating conditions that do not belong to the preset effective operating condition category on the evaluation results, thereby improving the representativeness of the unit product flue gas treatment carbon footprint of the evaluation object.

[0021] This invention generates status witnesses based on product output data, governance operation data, emission compliance status, data quality level, operating condition category, accounting model version, and accounting rule version within the accounting window. These status witnesses are then written into the blockchain, establishing a corresponding association between the data, status, and accounting basis of the accounting window. When subsequently obtaining status witnesses for multiple accounting windows corresponding to an evaluation object, new status witnesses to be verified can be generated and compared with the status witnesses written into the blockchain. This determines whether the data and status of the accounting window have passed integrity verification, improving the credibility, traceability, and verifiability of carbon footprint accounting results.

[0022] This invention further obtains the benchmark unit product flue gas treatment carbon footprint corresponding to the benchmark object, and generates low-carbon performance verification results based on the comparison results between the unit product flue gas treatment carbon footprint of the evaluation object and the benchmark unit product flue gas treatment carbon footprint. Therefore, this invention is applicable to benchmark objects such as historical operating periods, initial commissioning benchmark periods, design guarantee values, contractual target values, industry benchmark values, benchmark values ​​of similar devices, or operating periods before retrofitting. It is also applicable to evaluation objects such as current operating cycles, commissioning assessment periods, operation and maintenance service periods, low-carbon optimized operating periods, contract acceptance periods, monthly accounting periods, quarterly accounting periods, annual accounting periods, or operating periods after retrofitting. This provides a reliable evaluation basis for low-carbon retrofitting, operational optimization, contractual energy-saving and carbon-reduction services, and third-party verification.

[0023] The system of this invention collects product output data of the target production line and treatment operation data of the flue gas treatment system through edge acquisition nodes, writes and obtains status witnesses through blockchain interaction nodes, and completes carbon footprint accounting and low-carbon performance verification by executing corresponding computer programs through the processor. It can realize the automated execution of the above methods, which is conducive to improving the continuity, standardization and engineering applicability of carbon footprint accounting and low-carbon performance verification of industrial flue gas treatment systems.

[0024] The present invention will now be further described in conjunction with the accompanying drawings and specific embodiments. Additional aspects and advantages of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice. Attached Figure Description

[0025] The accompanying drawings, which form part of this specification, are used to aid in understanding the invention. The contents provided in the drawings and their related descriptions in this specification can be used to explain the invention, but do not constitute an undue limitation of the invention.

[0026] Figure 1 This is a schematic diagram illustrating the principle of a method for carbon footprint accounting and low-carbon performance verification of an industrial flue gas treatment system based on blockchain state witnessing, according to an embodiment of the present invention.

[0027] Figure 2 This is a schematic diagram of the structure of a blockchain-based industrial flue gas treatment system for carbon footprint accounting and low-carbon performance verification, according to an embodiment of the present invention.

[0028] Figure 3 This is a schematic diagram illustrating how an accounting window is divided into sub-accounting windows according to the time points when the working condition category changes, as described in an embodiment of the present invention.

[0029] Figure 4 This is a schematic diagram illustrating the process of generating a state witness, writing it into the blockchain, regenerating the state witness to be verified, and performing a consistency comparison in an embodiment of the present invention.

[0030] Figure 5 is a schematic structural diagram of an accounting window data packet in an embodiment of the present invention.

[0031] The marks in the figure are: edge collection node 11, processor 12, memory 13, and blockchain interaction node 14. DETAILED DESCRIPTION

[0032] The present invention will be clearly and completely described below with reference to the accompanying drawings. It should be understood that the following embodiments are used to illustrate the present invention, and are not intended to unduly limit the protection scope of the present invention. In the case of no conflict, the technical features in each embodiment described in this specification can be combined with each other. The term "comprising" and its similar terms used in this specification have an open meaning.

[0033] This embodiment is described by taking a target industrial production line and its supporting flue gas treatment system as an example. The to-be-treated flue gas generated by the target production line enters the flue gas treatment system, and the flue gas treatment system sequentially includes an activated carbon catalytic desulfurization section and a low-temperature SCR denitration section according to the flue gas flow direction. The to-be-treated flue gas first enters the activated carbon catalytic desulfurization section for desulfurization treatment, the desulfurized flue gas then enters the low-temperature SCR denitration section for denitration treatment, and the denitrated flue gas is discharged after being monitored by a continuous emission monitoring system.

[0034] In this embodiment, the activated carbon catalytic desulfurization section includes a desulfurization reactor, an activated carbon catalyst loading space located in the desulfurization reactor, a desulfurization catalyst regenerant spraying device for supplying regenerant to the activated carbon catalyst loading space, a regenerant circulation device for conveying or circulating the regenerant, a regenerant discharge device for discharging the regenerant, as well as fans, pumps and valves supporting the activated carbon catalytic desulfurization section. The activated carbon catalyst is used for catalytic desulfurization treatment of sulfur dioxide in the flue gas. After the activated carbon catalyst operates for a period of time, it is periodically sprayed and regenerated by the desulfurization catalyst regenerant spraying device to restore or maintain the desulfurization capacity of the activated carbon catalyst. The low-temperature SCR denitration section includes a low-temperature SCR denitration reactor, a reducing agent supply device, a reducing agent injection device, a low-temperature SCR denitration catalyst unit, as well as fans, valves and monitoring devices supporting the low-temperature SCR denitration section. The desulfurized flue gas is mixed with the reducing agent in the low-temperature SCR denitration section and passes through the low-temperature SCR denitration catalyst unit to reduce the content of nitrogen oxides in the flue gas. The principles and structures of the above activated carbon catalytic desulfurization section and low-temperature SCR denitration section have been disclosed in detail in a number of published patent applications of the applicant, and will not be repeated here.

[0035] as Figure 2As shown, the industrial flue gas treatment system carbon footprint accounting and low-carbon performance verification system based on blockchain status witnessing includes an edge acquisition node 11, a processor 12, a memory 13, and a blockchain interaction node 14. The edge acquisition node 11 is used to collect product output data from the target production line and treatment operation data of the flue gas treatment system. The processor 12 is used to perform carbon emission calculation, unit product flue gas treatment carbon footprint calculation, status determination, status witness generation, effective accounting window screening, evaluation object summary calculation, and low-carbon performance verification. The memory 13 is used to store computer programs, product output data, treatment operation data, carbon emission factors, accounting model version, accounting rule version, pollutant emission limit data, data quality level judgment rules, operating condition category judgment rules, preset effective operating condition categories, preset low-carbon performance thresholds, and preset window requirements. The blockchain interaction node 14 is used to write status witnesses to the blockchain and obtain status witnesses for multiple accounting windows corresponding to the evaluation objects from the blockchain.

[0036] Edge acquisition node 11 communicates with the production management system of the target production line to collect product output data. Edge acquisition node 11 also communicates with the data sources corresponding to the distributed control system, continuous emission monitoring system, metering devices, and equipment operation logs of the flue gas treatment system to collect treatment operation data of the flue gas treatment system. Edge acquisition node 11 can perform time synchronization, unit conversion, cumulative calculation, missing value marking, outlier marking, and time alignment, enabling data from different data sources to be mapped to the same accounting window. Edge acquisition node 11 can also sign the collected data to form an edge acquisition node signature for subsequent status witness generation.

[0037] like Figure 1 As shown, the method for carbon footprint accounting and low-carbon performance verification of industrial flue gas treatment system based on blockchain state witnessing in this embodiment includes the following steps executed sequentially: dividing the accounting window, data acquisition, carbon emission calculation, carbon footprint calculation of flue gas treatment per unit product, state determination, state witness generation and on-chaining, effective accounting window screening, evaluation object summary calculation, and low-carbon performance verification. Figure 1 The right side displays product output data, activity data, environmental compliance data, metering status data, and operating condition data. These five data types are arranged parallel to the data acquisition steps to illustrate the data types involved in each step. The vertical lines corresponding to each data type indicate its source or extension in subsequent processing. Horizontal arrows pointing from the data lines to the left-hand step boxes indicate a usage relationship between the data type and the corresponding step. Locations without horizontal arrows indicate that the data type does not directly participate in the processing of the corresponding step.

[0038] Step 1: Divide the accounting window.

[0039] Processor 12 divides the target production line's operating time into multiple accounting windows. These windows can be divided by hour, shift, day, production batch, or evaluation cycle. Each accounting window has an accounting window identifier, start time, end time, and target production line identifier. The accounting window identifier can be obtained by normalizing and concatenating the target production line identifier, start time, end time, and accounting rule version, followed by hash digest processing. By dividing the accounting windows, product output data, governance operation data, emission compliance status, data quality level, operating condition category, and status verification all correspond to a defined time range.

[0040] like Figure 3 As shown, when there are two or more operating condition categories within the same accounting window, the processor 12 can further divide the accounting window into two or more sub-accounting windows based on the time point when the operating condition category changes. Each sub-accounting window belongs to a time interval within the corresponding accounting window and is used to carry product output data, governance operation data, emission compliance status, data quality level, and operating condition category within the corresponding time interval when an operating condition switch occurs.

[0041] Step 2: Data collection.

[0042] Edge acquisition node 11 collects product output data of the target production line within each accounting window, and also collects the treatment operation data of the flue gas treatment system. Figure 1 In this configuration, product output data, activity data, environmental compliance data, metering status data, and operating condition data are set alongside the data collection steps, indicating that the data collection steps require the collection of these five types of data. Product output data refers to the output of the target production line within the calculation window, denoted as Q(T). Governance operation data includes activity data, environmental compliance data, metering status data, and operating condition data.

[0043] The activity data includes resource consumption data characterizing the carbon emissions generated by the flue gas treatment system within the accounting window, and, where recycling deductions exist, recycling deduction data characterizing the carbon emission deduction status. In this embodiment, the resource consumption data includes the power consumption of the activated carbon catalytic desulfurization section, the power consumption of the regenerated liquid circulation equipment, the power consumption of the desulfurization catalyst regenerated liquid spraying device, the regenerated liquid consumption, the makeup water consumption, the amount of activated carbon catalyst replenishment or replacement, the power consumption of the low-temperature SCR denitrification section, the reducing agent consumption, the compressed air consumption, and the amount of low-temperature SCR denitrification catalyst replenishment or replacement. If the flue gas treatment system is equipped with waste heat recovery equipment, the recycling deduction data includes the amount of waste heat recovered within the accounting window or the deduction amount calculated from the amount of waste heat recovered. Since activated carbon catalysts are currently replenished or replaced periodically during shutdown maintenance, the replenishment or replacement amount of activated carbon catalysts can be a preset value determined based on the maintenance plan, catalyst loading amount, usage cycle, or replacement record; similarly, the replenishment or replacement amount of low-temperature SCR denitrification catalysts can be a preset value determined based on the maintenance plan, catalyst loading amount, usage cycle, or replacement record.

[0044] Since the activated carbon catalytic desulfurization section requires periodic spray regeneration, this embodiment incorporates regeneration-related data as a crucial component of both activity data and operational status data. Regeneration-related activity data includes regenerated liquid consumption, power consumption of the regenerated liquid circulation equipment, spray pump operating time, regenerated liquid discharge, regenerated liquid reuse, and makeup water consumption. Regeneration-related operational status data includes spray regeneration start time, spray regeneration end time, spray regeneration status, regenerated liquid circulation status, regenerated liquid discharge status, and the operating status of the desulfurization reactor during spray regeneration. By including the spray regeneration process in the data acquisition and status determination within the accounting window, the differences in activity data and operational status data between the activated carbon catalytic desulfurization section under normal desulfurization and spray regeneration operating conditions can be distinguished.

[0045] Environmental compliance data includes measured pollutant emission data used to characterize the actual emission levels of pollutants within the accounting window, and pollutant emission limit data used to determine the benchmark for pollutant compliance. In this embodiment, the measured pollutant emission data is provided by a continuous emission monitoring system and includes at least measured data for sulfur dioxide, nitrogen oxides, and particulate matter at the emission outlet. To facilitate characterization of the operation of the activated carbon catalytic desulfurization section and the low-temperature SCR denitrification section, the measured pollutant emission data may also include measured data for sulfur dioxide at the inlet and outlet of the activated carbon catalytic desulfurization section, and measured data for nitrogen oxides at the inlet and outlet of the low-temperature SCR denitrification section. The pollutant emission limit data is stored in memory 13 and corresponds to the version of the accounting rules.

[0046] The measurement status data includes data source status data to characterize the reliability of the data source, calibration or verification status data to characterize whether the measuring equipment has been calibrated or verified, and data integrity and abnormal status data to characterize whether the data is complete or abnormal. In this embodiment, the data source status data includes the data source type, data source device identifier, acquisition method, automatic acquisition flag, and manual entry flag for each type of product output data and governance operation data; the calibration or verification status data includes the calibration or verification validity period, calibration or verification results, and equipment status of output measuring devices, power measuring devices, regenerated liquid measuring devices, reducing agent measuring devices, continuous emission monitoring systems, and other measuring devices; the data integrity and abnormal status data includes the proportion of missing data within the accounting window, the number of outliers, the duration of outliers, communication interruption flag, data supplementation flag, and data freeze flag.

[0047] The operating status data includes equipment commissioning status data to determine whether the flue gas treatment system is put into operation along with the target production line, and operating condition data to determine whether the flue gas treatment system meets preset operating conditions. Operating condition data includes operating mode data, operating load data, and key operating parameter data. In this embodiment, the equipment commissioning status data includes the commissioning status of the activated carbon catalytic desulfurization section, the low-temperature SCR denitrification section, the desulfurization catalyst regeneration liquid spraying device, the regeneration liquid circulation equipment, the reducing agent supply equipment, the flue gas bypass status, the maintenance status, and the main fan operating status. Operating mode data includes normal operation mode, spray regeneration mode, low-load operation mode, start-stop transition mode, and maintenance mode. Operating load data includes flue gas flow rate, target production line load, activated carbon catalytic desulfurization section processing load, regeneration liquid spray flow rate, reducing agent injection rate, and main fan load. Key operating parameters include the inlet flue gas temperature of the activated carbon catalytic desulfurization section, the sulfur dioxide concentration at the outlet of the activated carbon catalytic desulfurization section, the inlet flue gas temperature of the low-temperature SCR denitrification section, the nitrogen oxide concentration at the outlet of the low-temperature SCR denitrification section, the pressure difference of the low-temperature SCR denitrification reactor, the oxygen content, the regenerated liquid flow rate, and the regenerated liquid spraying pressure.

[0048] In one specific implementation, the edge acquisition node 11 can receive data corresponding to the accounting window according to preset data access rules. The preset data access rules include interface field rules and / or data import field rules, at least used to define the basic fields of the accounting window, product output data fields, activity data fields, environmental compliance data fields, operating condition data fields, and metering status data fields. Specifically, the basic fields of the accounting window include the accounting window identifier, target production line identifier, start time, and end time; the product output data field includes product output data; the activity data field includes various activity data used to calculate carbon emissions; the environmental compliance data field includes measured pollutant emission data and pollutant emission limit data; the operating condition data field includes equipment commissioning status data, operating mode data, operating load data, key operating parameter data, flue gas bypass status, and maintenance status; and the metering status data field includes data source status data, calibration or verification status data, data missing ratio, and number of outliers. After receiving data, edge acquisition node 11 verifies field completeness, field type, unit of measurement, time range, and data source identifier. When a field is missing, the field type does not conform to the preset field type, the unit of measurement is inconsistent, the time range is mismatched, or the data source identifier is missing, a missing or abnormal marker is generated for the corresponding data, and the missing or abnormal marker is included as part of the metering status data. The preset data access rules include interface field rules and / or data import field rules, which mean that edge acquisition node 11 can receive data from different sources according to preset data field requirements. Among them, interface field rules are used to constrain data automatically accessed through system interfaces, which can be data interfaces corresponding to production management systems, distributed control systems, continuous emission monitoring systems, or metering devices; data import field rules are used to constrain data received through data files, data tables, or other import methods. Both interface field rules and data import field rules can limit field names, field types, units of measurement, time formats, time granularity, data source identifiers, required fields, and optional fields, so that automatically accessed data and imported data can enter the accounting window or sub-accounting window according to the same data caliber, and are used for subsequent data quality level determination and status witness generation.

[0049] Step 3: Calculate carbon emissions.

[0050] The processor 12 calculates the carbon emissions of the flue gas treatment system within the accounting window based on the activity data and the carbon emission factor corresponding to the activity data. Figure 1In the diagram, activity data is linked to carbon emission calculation steps via horizontal arrows, indicating that the activity data is used for that step. Carbon emission factors correspond to the accounting rule versions and are stored in memory 13. For the power consumption of the activated carbon catalytic desulfurization section, the power consumption of the regenerated liquid circulation equipment, the power consumption of the desulfurization catalyst regenerated liquid spraying device, and the power consumption of the low-temperature SCR denitrification section, the corresponding power carbon emission factor can be retrieved; for the consumption of regenerated liquid, the replenishment or replacement of activated carbon catalyst, the consumption of reducing agent, and the replenishment or replacement of low-temperature SCR denitrification catalyst, the corresponding material carbon emission factor can be retrieved; for recycling deduction data, negative carbon emission factors can be retrieved or deductions can be made according to preset deduction rules.

[0051] In this embodiment, the carbon emissions of the flue gas treatment system within the accounting window are calculated according to the following formula:

[0052] E(T)=ΣA i (T)×EF i i = 1, 2, ..., n

[0053] In the formula, T represents the accounting window, E(T) represents the carbon emissions of the flue gas treatment system within the accounting window T, and A i (T) represents the i-th type of activity data within the accounting window T, EF i Let represent the carbon emission factor corresponding to the i-th type of activity data, n represent the number of activity data types, and Σ represent the summation of all types of activity data for i = 1, 2, ..., n. When the i-th type of activity data is recycling deduction data, the corresponding carbon emission factor is negative, or it is deducted according to the preset deduction rules.

[0054] Step 4: Calculate the carbon footprint of flue gas treatment per unit product.

[0055] When the product output within the accounting window is greater than zero, the processor 12 divides the carbon emissions of the flue gas treatment system within the accounting window by the product output within the accounting window to obtain the carbon footprint of flue gas treatment per unit product within the accounting window. Figure 1 In this embodiment, product output data is linked to the unit product flue gas treatment carbon footprint calculation step via horizontal arrows, indicating that the product output data is used for this step. The unit product flue gas treatment carbon footprint within this calculation window is calculated using the following formula:

[0056] I(T) = E(T) / Q(T)

[0057] In the formula, I(T) represents the carbon footprint of flue gas treatment per unit product within the accounting window T, E(T) represents the carbon emissions of the flue gas treatment system within the accounting window T, and Q(T) represents the product output within the accounting window T, where Q(T) > 0. When Q(T) = 0, the processor 12 does not calculate the carbon footprint of flue gas treatment per unit product within this accounting window and treats this accounting window as an accounting window that cannot participate in the summary calculation of the evaluation objects.

[0058] Step 5: Status determination.

[0059] The processor 12 determines the emission compliance status of the accounting window based on the environmental compliance data, determines the data quality level of the accounting window based on the metering status data, and determines the operating condition category of the accounting window based on the operating condition status data. Figure 1 In the diagram, environmental compliance data, metering status data, and operating condition status data are linked to the status determination step via horizontal arrows, indicating that the above data is used in that step.

[0060] Specifically, the processor 12 compares the measured data of sulfur dioxide, nitrogen oxides, and particulate matter within the calculation window with the corresponding emission limits for each pollutant. When all measured emission data for each pollutant meets the corresponding emission limit, the emission compliance status is "compliant"; when any measured emission data for any pollutant does not meet the corresponding emission limit, the emission compliance status is "non-compliant". For the calculation window where the activated carbon catalytic desulfurization section is in spray regeneration mode, the processor 12 still determines the emission compliance status based on the measured pollutant emission data at the emission outlet. If the spray regeneration process causes abnormal measured pollutant emission data or missing data from the continuous emission monitoring system, the data quality level is determined by combining data integrity and abnormal data.

[0061] The rules for determining emission compliance status can be configured according to the version of the accounting rules. Different target production lines, different flue gas treatment systems, different evaluation objects, or different applicable emission standards may correspond to different pollutant emission limit data. The processor 12 can call the corresponding pollutant type, monitoring point, statistical caliber, emission limit data, and compliance determination method according to the current version of the accounting rules. The compliance determination method may include judging the average value, maximum value, cumulative exceedance time, or proportion of valid monitoring data of the measured pollutant emission data within the accounting window. After the status witness of the corresponding accounting window or sub-accounting window is generated, the rules for determining emission compliance status are associated with the version of the accounting rules and the version of the pollutant emission limit data, so that the emission compliance status can be re-determined according to the same rules during subsequent integrity verification.

[0062] Processor 12 determines the data quality level of the accounting window based on the measurement status data. The data quality level is jointly determined by the data source status data, calibration or verification status data, and data integrity and abnormal status data. Processor 12 generates data quality codes for product output data and governance operation data according to the data quality level judgment rules in the accounting rule version. The data quality codes include data source codes, calibration or verification codes, and integrity abnormality codes. Processor 12 generates the data quality level of the accounting window based on the data quality codes. Only when the data quality level meets the preset requirements is the accounting window allowed to participate in the selection of valid accounting windows.

[0063] The processor 12 determines the operating condition category of the calculation window based on the operating condition status data. In this embodiment, the operating condition category includes effective operating conditions and ineffective operating conditions. Effective operating conditions are those where the flue gas treatment system is put into operation with the target production line and meets preset operating conditions, while ineffective operating conditions are those where the flue gas treatment system is not put into operation with the target production line or does not meet preset operating conditions. When the target production line is in production, the activated carbon catalytic desulfurization section is in operation, the low-temperature SCR denitrification section is in operation, the flue gas bypass status is not bypassed, the maintenance status is not under maintenance, the operating mode data is normal operation mode or spray regeneration mode that meets the requirements of the calculation rule version, and the key operating parameters such as flue gas flow rate, inlet flue gas temperature of the activated carbon catalytic desulfurization section, inlet flue gas temperature of the low-temperature SCR denitrification section, pressure difference of the low-temperature SCR denitrification reactor, regenerated liquid spray pressure, and reducing agent injection amount are within the preset range, the processor 12 determines that the operating condition category of the calculation window is an effective operating condition; otherwise, the processor 12 determines that the operating condition category of the calculation window is an ineffective operating condition.

[0064] For the spray regeneration mode, this embodiment can set rules for determining the effective operating conditions of regeneration. If the target production line is still in production under the spray regeneration mode, the activated carbon catalytic desulfurization section and the low-temperature SCR denitrification section are still in operation with the target production line, the emission compliance status is compliant, and the regenerated liquid spray flow rate, regenerated liquid spray pressure, and regenerated liquid circulation equipment operation status meet the preset operating conditions, then the spray regeneration mode can be classified as a preset effective operating condition. If the corresponding flue gas treatment system is shut down, the flue gas is bypassed, under maintenance, or the pollutant emissions are not compliant, then the spray regeneration mode does not belong to the preset effective operating condition category.

[0065] In one specific implementation, when there are two or more operating condition categories within the same accounting window, the processor 12 divides the accounting window into two or more sub-accounting windows based on the time point when the operating condition category changes. The time point when the operating condition category changes can be determined based on operating mode data, treatment equipment commissioning status data, flue gas bypass status, maintenance status, operating load data, and key operating parameter data. For example, when two or more operating modes, such as normal operation mode, spray regeneration mode, low load operation mode, start-stop transition mode, or maintenance mode, appear sequentially within the same accounting window, the processor 12 can determine the dividing point based on the start and end times of the corresponding operating modes.

[0066] For each sub-accounting window, the processor 12 determines the product output data, treatment operation data, emission compliance status, data quality level, and operating condition category within that sub-accounting window, and calculates the carbon emissions of the flue gas treatment system within that sub-accounting window, generating corresponding status witnesses. Subsequent effective accounting window screening, evaluation object aggregation calculation, and low-carbon performance verification use these sub-accounting windows as processing objects for screening and aggregation calculations. This avoids the mixing of effective and ineffective operating conditions within the same accounting window for evaluation, and also prevents the simple inclusion of the impact of spray regeneration mode, start-stop transition mode, or maintenance mode on the carbon footprint of flue gas treatment per unit product into the normal operation mode.

[0067] like Figure 3 As shown, the calculation window T represents a calculation window within the target production line's operating time. When the operating condition category within this calculation window T changes, the processor 12 uses the time point of the change in operating condition category as the dividing point to divide the calculation window T into multiple consecutive sub-calculation windows, such as sub-calculation window T1, sub-calculation window T2, and sub-calculation window T3. Sub-calculation window T1 corresponds to valid operating conditions, sub-calculation window T2 corresponds to the spray regeneration mode that meets the requirements of the calculation rule version and can be considered a valid operating condition, and sub-calculation window T3 corresponds to invalid operating conditions. Figure 3 The time axis located below the accounting window T represents the continuity of accounting window T in the time direction. The vertical dividing lines on the time axis represent the time points when the operating condition category changes. The sub-accounting windows below accounting window T represent different time intervals formed according to the dividing points. Each sub-accounting window has a corresponding start time, end time, product output data, governance operation data, emission compliance status, data quality level, and operating condition category. Figure 3 This explanation uses three sub-calculation windows as an example. In practical applications, the number of sub-calculation windows can be determined based on the number of times the operating condition category changes within the calculation window.

[0068] When determining the product output data and governance operation data of the sub-accounting window, the processor 12 can read the data within the corresponding time interval from the original collected data with timestamps based on the start and end times of the sub-accounting window. For data collected in the form of cumulative values, the processor 12 can determine the amount of data within the sub-accounting window based on the difference in cumulative readings corresponding to the start and end times of the sub-accounting window. For data collected in the form of instantaneous values ​​or periodic sampled values, the processor 12 can determine the statistical value within the sub-accounting window based on the sampled data falling within the sub-accounting window. Thus, the product output data, activity data, environmental compliance data, metering status data, and operating condition status data of the sub-accounting window can all have corresponding time ranges.

[0069] Step 6: State witness generation and on-chain.

[0070] The processor 12 generates a status witness to prove that the data and status of the accounting window have not been tampered with, based on the product output data, governance operation data, emission compliance status, data quality level, operating condition category, accounting model version, and accounting rule version within the accounting window, and writes the status witness into the blockchain through the blockchain interaction node 14. Figure 1 In the process, product output data, activity data, environmental compliance data, metering status data, and operating condition status data are all linked to the status witness generation and on-chain steps via horizontal arrows, indicating that the above data are all related to the status witness generation.

[0071] Before generating status witnesses, processor 12 first performs standardized encoding on product output data and governance operation data. Standardized encoding uses a unified field order, unified time format, unified numerical precision, and unified units. After standardized encoding, product output data, activity data, environmental compliance data, metering status data, and operating condition status data are written into the accounting window data packet in the form of corresponding fields. For example... Figure 5As shown, the standardized coded accounting window data package includes window basic fields, product output data fields, activity data fields, environmental compliance data fields, metering status data fields, operating condition status data fields, and version fields. The window basic fields include the accounting window identifier, target production line identifier, start time, and end time. The product output data field records product output data and includes product output, output unit, output data source, and output metering device identifier. The activity data field records activity data and includes activity data type code, activity data value, activity data unit, carbon emission factor identifier, carbon emission factor version, and data source. The environmental compliance data field records environmental compliance data and includes pollutant type code, measured pollutant emission data, pollutant emission limit data, monitoring point identifier, and continuous emission monitoring system information. The system includes a unified identifier; a metering status data field to record metering status data, including data source code, calibration or verification code, and integrity anomaly code; an operating condition status data field to record operating condition data, including activated carbon catalytic desulfurization section commissioning status code, low-temperature SCR denitrification section commissioning status code, spray regeneration status code, operation mode code, operating load code, key operating parameter code, flue gas bypass status code, and maintenance status code; and a version field including the accounting model version and accounting rule version, and may also include carbon emission factor version, pollutant emission limit data version, data structure version, and status witness contract version. When generating a status witness, the processor 12 associates and records the accounting model version, accounting rule version, carbon emission factor version, pollutant emission limit data version, data structure version, and status witness contract version. The above version information is frozen after the status witness is generated in the corresponding accounting window or sub-accounting window. If the accounting model, accounting rules, carbon emission factors, pollutant emission limit data, data structure, or status witness contract are subsequently updated, processor 12 generates a new version identifier for the updated content and uses the new version identifier in the new accounting window or sub-accounting window. This avoids mixing different version rules in the same status witness, facilitating subsequent audit tracking and consistency verification.

[0072] like Figure 4As shown, processor 12 performs hash digest processing on the product output data and governance operation data within the accounting window to obtain a data evidence digest. The governance operation data includes activity data, environmental compliance data, metering status data, and operating condition status data. In the accounting window data package, product output data, activity data, environmental compliance data, metering status data, and operating condition status data are recorded as product output data fields, activity data fields, environmental compliance data fields, metering status data fields, and operating condition status data fields, respectively. Specifically, processor 12 performs hash digest processing on the product output data fields, activity data fields, environmental compliance data fields, metering status data fields, and operating condition status data fields to obtain product output data digests, activity data digests, environmental compliance data digests, metering status data digests, and operating condition status data digests, respectively. Then, these digests are concatenated with the accounting window identifier in a preset order and hash digest processing is performed to obtain a data evidence digest. Processor 12 also performs hash digest processing on the emission compliance status, data quality level, operating condition category, accounting model version, and accounting rule version of the accounting window to obtain a status digest. Specifically, processor 12 normalizes and encodes the emission compliance status, data quality level, operating condition category, accounting model version, and accounting rule version according to a preset field order, then concatenates them and performs hash digest processing to obtain a status digest. The status digest characterizes the status of the accounting window in terms of emission compliance, data quality, operating condition category, and accounting basis version. Processor 12 generates a status witness based on the data evidence digest, status digest, accounting window identifier, target production line identifier, and edge acquisition node signature. The status witness can be generated in the following field order: accounting window identifier, target production line identifier, data evidence digest, status digest, previous accounting window status witness digest, edge acquisition node identifier, and edge acquisition node signature. The previous accounting window status witness digest is a digest of the status witness corresponding to the previous accounting window of the same target production line. Thus, multiple accounting windows corresponding to the same target production line can form a time-sequentially associated sequence of status witnesses.

[0073] When an accounting window is divided into two or more sub-accounting windows, the processor 12 can generate a sub-accounting window identifier for each sub-accounting window. The sub-accounting window identifier can be obtained by normalizing and concatenating the accounting window identifier, sub-accounting window start time, sub-accounting window end time, and operating condition category, followed by hash digest processing. The processor 12 generates a data evidence digest, a status digest, and a status witness for each sub-accounting window. At this time, the status witness is associated with the corresponding product output data, governance operation data, emission compliance status, data quality level, operating condition category, accounting model version, and accounting rule version of the sub-accounting window. The blockchain interaction node 14 writes the status witness corresponding to each sub-accounting window into the blockchain for subsequent integrity verification and effective accounting window selection according to the sub-accounting window.

[0074] In this embodiment, the blockchain can be in the form of a consortium blockchain. The consortium blockchain can be a newly established consortium blockchain for this system, or it can be an existing blockchain network deployed by the enterprise to which the target production line belongs, the operation and maintenance service provider of the flue gas treatment system, a third-party verification party, or an industrial internet platform. Enterprise nodes, operation and maintenance service nodes, and verification nodes can be set up in the consortium blockchain. Enterprise nodes are used to submit status witnesses for the corresponding accounting window or sub-accounting window of the target production line and flue gas treatment system; operation and maintenance service nodes are used to submit or query status witnesses related to low-carbon optimized operation during the operation and maintenance service period; verification nodes are used to query on-chain status witnesses, on-chain transaction identifiers, and on-chain receipts, and cooperate with processor 12 to perform integrity verification.

[0075] State witness contracts can be deployed in a consortium blockchain. These contracts are used to receive, verify, store, and query state witnesses. A state witness contract includes at least a write interface, a query interface, and an evaluation object index interface. Before writing a state witness, blockchain interaction node 14 can verify whether the edge acquisition node signature matches the edge acquisition node identifier. After successful verification, it calls the write interface of the state witness contract to write the state witness to the blockchain. The state witness contract records on-chain the accounting window identifier, target production line identifier, state witness, data evidence digest, state digest, edge acquisition node signature, write time, and on-chain transaction identifier.

[0076] When using an existing blockchain network, blockchain interaction node 14 can configure the chain identifier, node access address, account certificate, signature certificate, state witness contract address, or evidence storage interface address according to the access specifications of the existing blockchain network. If the existing blockchain network supports the deployment of state witness contracts, blockchain interaction node 14 can call the write interface, query interface, and evaluation object index interface of the state witness contract; if the existing blockchain network has provided evidence storage contract or data digest write interface, blockchain interaction node 14 can also write the state witness, data evidence digest, state digest, accounting window identifier, target production line identifier, and edge acquisition node signature into the existing blockchain network according to the existing interface requirements. The transaction hash, block height, write time, or evidence storage number returned by the existing blockchain network can be used as an on-chain receipt, associated with the corresponding accounting window identifier or sub-accounting window identifier, and saved for subsequent integrity verification and third-party verification.

[0077] To reduce the risk of leakage of raw production data and environmental monitoring data, the consortium blockchain can record only state witnesses, data evidence summaries, state summaries, accounting window identifiers, target production line identifiers, edge acquisition node signatures, write times, on-chain transaction identifiers, and on-chain receipts. The original product output data and governance operation data are stored in the enterprise-side database or audit data warehouse. During subsequent integrity verification, the processor 12 reads the corresponding off-chain data and regenerates the state witness to be verified, and then performs a consistency comparison with the on-chain state witness.

[0078] After the state witness is written to the blockchain, the blockchain interaction node 14 receives an on-chain receipt. The on-chain receipt may include the transaction hash, block height, write time, state witness contract version, and event log. The processor 12 associates and saves the on-chain receipt with the corresponding accounting window identifier or sub-accounting window identifier, and uses the on-chain receipt as an index for querying the on-chain state witness during subsequent integrity verification and third-party verification.

[0079] Step 7: Filter the valid accounting window.

[0080] When it is necessary to calculate the carbon footprint of flue gas treatment per unit product or verify the low-carbon performance of the evaluation object, the processor 12 first determines the target production line identifier, evaluation start time, evaluation end time, and evaluation object identifier corresponding to the evaluation object, and then determines a set of candidate accounting windows based on the target production line identifier, evaluation start time, and evaluation end time. The set of candidate accounting windows includes accounting windows whose time range falls within the evaluation object; when an accounting window is divided into two or more sub-accounting windows, the set of candidate accounting windows may also include sub-accounting windows whose time range falls within the evaluation object. The processor 12 queries and obtains the corresponding status witness through the blockchain interaction node 14 based on the accounting window identifier or sub-accounting window identifier in the set of candidate accounting windows. Accounting windows or sub-accounting windows for which no corresponding status witness is found can be marked as pending review and do not participate in the selection of valid accounting windows.

[0081] After obtaining the status witnesses corresponding to the candidate accounting window set, the processor 12 performs integrity verification on the status witnesses and selects valid accounting windows from the candidate accounting window set based on the product output data, emission compliance status, data quality level and operating condition category corresponding to the status witnesses that have passed integrity verification. Figure 1 In this process, product output data, environmental compliance data, metering status data, and operating condition status data are all associated with the effective accounting window screening step via horizontal arrows, indicating that the above data and their corresponding status are used in this step. After obtaining the status witnesses of multiple accounting windows corresponding to the evaluation object, the processor 12 reads the product output data, governance operation data, emission compliance status, data quality level, and operating condition category corresponding to the status witness according to the accounting window identifier. The processor 12 re-executes normalization encoding and hash digest processing on the read data and status according to the hash digest processing rules used when generating the status witness, and regenerates the status witness to be verified. The processor 12 performs a consistency comparison between the status witness to be verified and the status witness written to the blockchain. When the status witness to be verified is consistent with the status witness written to the blockchain, it is determined that the data and status of the accounting window have passed the integrity verification, and the accounting window is allowed to participate in the effective accounting window screening; when the status witness to be verified is inconsistent with the status witness written to the blockchain, it is determined that the data and status of the accounting window have not passed the integrity verification, and the accounting window is prohibited from participating in the effective accounting window screening.

[0082] When the state witness to be verified is inconsistent with the state witness written to the blockchain, the processor 12 can also generate a verification anomaly record. The verification anomaly record includes an accounting window identifier or a sub-accounting window identifier, an on-chain receipt, a regenerated data evidence digest, a regenerated state digest, the inconsistency field type, and the verification time. The processor 12 can generate an anomaly review task based on the verification anomaly record and mark the corresponding accounting window or sub-accounting window as pending review; accounting windows or sub-accounting windows in the pending review state do not participate in the selection of valid accounting windows.

[0083] An effective accounting window is an accounting window where product output is greater than zero, emissions compliance status is compliant, data quality level meets preset requirements, and operating condition category belongs to a preset effective operating condition category. In this embodiment, the preset effective operating condition category includes effective operating conditions. When the same accounting window is divided into two or more sub-accounting windows, the processor 12 uses the sub-accounting window as the processing object for filtering effective accounting windows; if the product output of the sub-accounting window is greater than zero, emissions compliance status is compliant, data quality level meets preset requirements, and operating condition category belongs to a preset effective operating condition category, then the sub-accounting window is considered an effective accounting window; if the sub-accounting window does not meet the above conditions, then the sub-accounting window is marked as an ineffective accounting window, or the carbon emissions of the flue gas treatment system within the sub-accounting window are aggregated into ineffective operating condition carbon emissions.

[0084] When an accounting window is not divided into sub-accounting windows, and the operating condition category of that accounting window is an ineffective operating condition, the processor 12 marks the accounting window as an ineffective accounting window, or aggregates the carbon emissions of the flue gas treatment system within that accounting window as ineffective operating condition carbon emissions. Ineffective operating condition carbon emissions can be stored as supplementary statistical data, but are not included in the calculation of the unit product flue gas treatment carbon footprint of the evaluation object.

[0085] Step 8: Summarize and calculate the evaluation objects.

[0086] Processor 12 divides the total carbon emissions of the flue gas treatment system within the effective accounting window by the total product output within the effective accounting window to obtain the unit product flue gas treatment carbon footprint of the evaluated object. Figure 1 In the calculation, product output data and activity data are linked to the summary calculation step of the evaluation object via horizontal arrows, indicating that the product output data and the carbon emissions of the flue gas treatment system calculated from the activity data are used together in this step. Let the effective accounting window set be Ω, and the carbon footprint of the evaluation object's unit product flue gas treatment is calculated according to the following formula:

[0087] I e =ΣE(T) / ΣQ(T), T∈Ω

[0088] In the formula, I eLet Ω represent the carbon footprint of flue gas treatment per unit product of the evaluated object, Σ represent the set of effective accounting windows, Σ represent the summation of all effective accounting windows in the set of effective accounting windows Ω, T represent an effective accounting window in the set of effective accounting windows Ω, E(T) represent the carbon emissions of the flue gas treatment system in the effective accounting window T, and Q(T) represent the product output in the effective accounting window T.

[0089] When an accounting window is divided into two or more sub-accounting windows, the effective accounting window set Ω can include sub-accounting windows that meet the conditions for an effective accounting window. In this case, T in the formula represents the accounting window or sub-accounting window participating in the summary calculation of the evaluation objects, E(T) represents the carbon emissions of the flue gas treatment system within the corresponding accounting window or sub-accounting window, and Q(T) represents the product output within the corresponding accounting window or sub-accounting window. Therefore, when summarizing the evaluation objects, only the time intervals that have passed integrity verification and meet the conditions for an effective accounting window can be summarized.

[0090] Step 9: Low-carbon performance verification.

[0091] Processor 12 acquires the baseline unit product flue gas treatment carbon footprint corresponding to the baseline object, and generates low-carbon performance verification results based on the comparison between the unit product flue gas treatment carbon footprint of the evaluation object and the baseline unit product flue gas treatment carbon footprint. In this embodiment, the baseline object can be the pre-modification operation period, and the evaluation object can be the post-modification operation period. Processor 12 calculates the low-carbon performance reduction rate according to the following formula:

[0092] η=(I b -I e ) / I b ×100%

[0093] In the formula, η represents the reduction in low-carbon performance, and I b Indicates the carbon footprint of flue gas treatment per unit of product, I e This represents the unit product flue gas treatment carbon footprint of the evaluated object. When the reduction in low-carbon performance reaches the preset low-carbon performance threshold, and the number or proportion of effective accounting windows meets the preset window requirements, the processor 12 generates a low-carbon performance verification pass result; when the reduction in low-carbon performance does not reach the preset low-carbon performance threshold, or the number or proportion of effective accounting windows does not meet the preset window requirements, the processor 12 generates a low-carbon performance verification fail result or a result pending review.

[0094] like Figure 2As shown, edge acquisition node 11, processor 12, memory 13, and blockchain interaction node 14 together constitute a blockchain-based industrial flue gas treatment system for carbon footprint accounting and low-carbon performance verification. Edge acquisition node 11 provides processor 12 with product output data and treatment operation data. Processor 12 calls the computer program, accounting model version, accounting rule version, carbon emission factor, pollutant emission limit data, and related judgment rules stored in memory 13 to execute... Figure 1 The processing steps are shown. Data reading and writing can be performed between processor 12 and memory 13. After generating a state witness, processor 12 writes the state witness to the blockchain through blockchain interaction node 14; during the summary calculation of evaluation objects and verification of low-carbon performance, processor 12 can also obtain the state witnesses of multiple accounting windows corresponding to the evaluation objects through blockchain interaction node 14. Figure 2 This is only used to illustrate the basic relationships between the components in the system, and does not require that the edge acquisition node 11, processor 12, memory 13 and blockchain interaction node 14 be located in the same physical device.

[0095] Through the above implementation methods, the resource consumption, environmental compliance, metering reliability, and operating conditions generated by the normal desulfurization operation, periodic spray regeneration operation, and denitrification operation of the activated carbon catalytic desulfurization section, as well as the denitrification operation of the low-temperature SCR denitrification section, can be correlated with the product output data of the target production line within the accounting window or sub-accounting window. Status witnessing can establish a verifiable correspondence between the data, status, and accounting basis within the accounting window or sub-accounting window. The unit product flue gas treatment carbon footprint of the evaluation object can be calculated based on a valid accounting window that has passed integrity verification and meets the conditions. The low-carbon performance verification results can be generated based on the comparison results between the unit product flue gas treatment carbon footprint of the evaluation object and the benchmark unit product flue gas treatment carbon footprint.

[0096] The foregoing has described the relevant content of this invention. Those skilled in the art will be able to implement this invention based on these descriptions. The specific time length, data fields, encoding methods, hash digest processing rules, blockchain type, state witness contract interface, and judgment thresholds in the above embodiments can be adjusted according to the actual situation of the target production line and flue gas treatment system, but should not be construed as limiting the scope of protection of this invention.

Claims

1. A method for carbon footprint accounting and low-carbon performance verification of industrial flue gas treatment systems based on blockchain state witnessing, characterized in that: include: S1. Divide the running time of the target production line into multiple accounting windows; S2. In each of the accounting windows, product output data of the target production line is collected, and treatment operation data of the flue gas treatment system is collected. The treatment operation data includes activity data for calculating carbon emissions, environmental compliance data for judging whether pollutants are discharged in compliance with standards, metering status data for judging whether the data is reliable, and operating status data for determining the operating condition category of the accounting window. S3. Calculate the carbon emissions of the flue gas treatment system within the accounting window based on the activity data and the carbon emission factor corresponding to the activity data; S4. When the product output in the accounting window is greater than zero, divide the carbon emissions of the flue gas treatment system in the accounting window by the product output in the accounting window to obtain the carbon footprint of flue gas treatment per unit product in the accounting window. S5. Determine the emission compliance status of the accounting window based on the environmental compliance data, determine the data quality level of the accounting window based on the metering status data, and determine the operating condition category of the accounting window based on the operating condition status data. S6. Based on the product output data, governance operation data, emission compliance status, data quality level, working condition category, accounting model version and accounting rule version in the accounting window, generate a status witness to prove that the data and status of the accounting window have not been tampered with, and write the status witness into the blockchain. S7. Obtain status witnesses for multiple accounting windows corresponding to the evaluation object, perform integrity verification on the status witnesses, and filter out valid accounting windows from the multiple accounting windows based on the product output data, emission compliance status, data quality level and operating condition category corresponding to the status witnesses that have passed integrity verification. The valid accounting window is an accounting window where the product output is greater than zero, the emission compliance status is compliant, the data quality level meets the preset requirements, the operating condition category belongs to the preset valid operating condition category, and the data and status have passed integrity verification. S8. Divide the total carbon emissions of the flue gas treatment system within the effective accounting window by the total product output within the effective accounting window to obtain the unit product flue gas treatment carbon footprint of the evaluation object. S9. Obtain the carbon footprint of flue gas treatment of the benchmark unit product corresponding to the benchmark object, and generate low-carbon performance verification results based on the comparison results between the carbon footprint of flue gas treatment of the evaluation object and the carbon footprint of flue gas treatment of the benchmark unit product.

2. The method as described in claim 1, characterized in that: The activity data includes resource consumption data to characterize the carbon emissions generated by the flue gas treatment system within the accounting window, and, when there are recycling deduction items, recycling deduction data to characterize the carbon emission deduction status. The environmental compliance data includes measured pollutant emission data used to characterize the actual emission level of pollutants within the accounting window, and pollutant emission limit data used to determine the benchmark for judging pollutant compliance. The metrological status data includes data source status data used to characterize whether the data source is reliable, calibration or verification status data used to characterize whether the metrological equipment has been calibrated or verified, and data integrity and abnormal status data used to characterize whether the data is complete or abnormal. The operating status data includes the operation status data of the treatment equipment used to determine whether the flue gas treatment system is put into operation along with the target production line, and the operating condition data used to determine whether the flue gas treatment system meets the preset operating conditions. The operating condition data includes operating mode data, operating load data, and key operating parameter data.

3. The method as described in claim 1, characterized in that: The carbon emissions of the flue gas treatment system within this accounting window are calculated using the following formula: E(T)=ΣA i (T)×EF i ,i=1,2,…,n In the formula, T represents the accounting window, E(T) represents the carbon emissions of the flue gas treatment system within the accounting window T, and A i (T) represents the i-th type of activity data within the accounting window T, EF i Σ represents the carbon emission factor corresponding to the i-th type of activity data, n represents the number of types of activity data, and Σ represents the summation of all types of activity data i = 1, 2, ..., n. When the i-th type of activity data is recycling deduction data, the corresponding carbon emission factor is negative or deducted according to the preset deduction rules.

4. The method as described in claim 3, characterized in that: The carbon footprint of flue gas treatment per unit product within this accounting window is calculated using the following formula: I(T) = E(T) / Q(T) In the formula, I(T) represents the carbon footprint of flue gas treatment per unit product within the accounting window T, E(T) represents the carbon emissions of the flue gas treatment system within the accounting window T, Q(T) represents the product output within the accounting window T, and Q(T) > 0.

5. The method as described in claim 1, characterized in that: Generating the state witness includes: The product output data and governance operation data within the accounting window are hash digested to obtain a data evidence digest. A hash digest is generated by processing the emission compliance status, data quality level, operating condition category, accounting model version, and accounting rule version of the accounting window. The status witness is generated based on the data evidence summary, status summary, accounting window identifier, target production line identifier, and edge acquisition node signature. The status witness is associated with the product output data, governance operation data, emission compliance status, data quality level and operating condition category of the accounting window.

6. The method as described in claim 5, characterized in that: After obtaining the status witnesses of multiple accounting windows corresponding to the evaluation object, the product output data, governance operation data, emission compliance status, data quality level and operating condition category corresponding to the status witness are read according to the accounting window identifier. Regenerate the state witness to be verified according to the hash digest processing rules used when generating the state witness; The consistency comparison between the state witness to be verified and the state witness written into the blockchain is performed. When the state witness to be verified is consistent with the state witness written to the blockchain, it is determined that the data and state of the accounting window have passed the integrity verification, and the accounting window is allowed to participate in the screening of valid accounting windows; When the state witness to be verified is inconsistent with the state witness written to the blockchain, it is determined that the data and state of the accounting window have not passed the integrity verification, and the accounting window is prohibited from participating in the screening of valid accounting windows.

7. The method as described in claim 1, characterized in that: The operating condition categories include effective operating conditions and ineffective operating conditions. The effective operating conditions are those in which the flue gas treatment system is put into operation with the target production line and meets the preset operating conditions. The ineffective operating conditions are those in which the flue gas treatment system is not put into operation with the target production line or does not meet the preset operating conditions. The preset effective operating condition category includes the effective operating conditions; When there are two or more operating condition categories within the same accounting window, the accounting window is divided into two or more sub-accounting windows based on the time point when the operating condition category changes. According to the start and end times of each sub-accounting window, the product output data, treatment operation data, emission compliance status, data quality level, and operating condition category of each sub-accounting window are determined. The carbon emissions of the flue gas treatment system within each sub-accounting window are calculated, and corresponding status verification is generated. The effective accounting window selection uses the sub-accounting windows as the selection objects, the evaluation object summary calculation is based on the selected sub-accounting windows, and the low-carbon performance verification is based on the results of the evaluation object summary calculation. When the operating condition category of the accounting window or sub-accounting window belongs to the non-effective operating condition, the accounting window or sub-accounting window is marked as a non-effective accounting window, or the carbon emissions of the flue gas treatment system in the accounting window or sub-accounting window are collected as non-effective operating condition carbon emissions.

8. The method as described in claim 1, characterized in that: The benchmark objects are historical operating periods, initial commissioning benchmark periods, design guarantee values, contractual target values, industry benchmark values, benchmark values ​​of similar equipment, or operating periods before modification; The evaluation objects are the current operating cycle, commissioning assessment period, operation and maintenance service period, low-carbon optimized operation period, contract acceptance period, monthly accounting period, quarterly accounting period, annual accounting period, or the operation period after modification.

9. The method as described in claim 1, characterized in that: Let the effective accounting window set be Ω, and the carbon footprint of the unit product flue gas treatment of the evaluated object be calculated according to the following formula: I e =ΣE(T) / ΣQ(T),T∈Ω In the formula, I e Let Ω represent the carbon footprint of flue gas treatment per unit product of the evaluated object, Σ represent the set of effective accounting windows, Σ represent the summation of all effective accounting windows in the set of effective accounting windows Ω, T represent an effective accounting window in the set of effective accounting windows Ω, E(T) represent the carbon emissions of the flue gas treatment system in the effective accounting window T, and Q(T) represent the product output in the effective accounting window T. The low-carbon performance verification result is determined based on the reduction rate of low-carbon performance, and the reduction rate of low-carbon performance is calculated according to η = (I b -I e ) / I b Calculated by multiplying by 100%, where η represents the reduction in low-carbon performance, and I b This represents the carbon footprint of flue gas treatment per unit of product. When the reduction in low-carbon performance reaches a preset low-carbon performance threshold, and the number or proportion of effective accounting windows meets the preset window requirements, a low-carbon performance verification result is generated.

10. A blockchain-based system for verifying the carbon footprint and low-carbon performance of industrial flue gas treatment systems, characterized in that: This includes edge acquisition nodes, blockchain interaction nodes, processors, and memory; The edge acquisition node is used to collect product output data of the target production line and treatment operation data of the flue gas treatment system. The blockchain interaction node is used to write state witnesses to the blockchain and obtain state witnesses of multiple accounting windows corresponding to the evaluation object from the blockchain. The memory stores computer programs; When the processor executes the computer program, it causes the system to perform the method of any one of claims 1 to 9.

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