Atmospheric pollution source organic emission source spectrum quality evaluation system

Abstract

This invention relates to the field of atmospheric environmental monitoring technology and discloses a source spectrum quality evaluation system for organic pollutant emissions from atmospheric pollution sources. The system includes a source spectrum data acquisition and preprocessing module, an industry classification and weight adaptive configuration module, a five-dimensional quality comprehensive evaluation module, an anomaly tracing and hierarchical diagnosis module, an intelligent correction and optimization module, and a result output and storage management module, all connected sequentially. Traditional verification only checks superficial issues such as missing data and format conformity, failing to identify core problems such as abnormal sampling conditions, distorted pollutant components, missing characteristic substances, and insufficient data stability. This system, relying on the five-dimensional quality comprehensive evaluation module, verifies data from five dimensions: compliance of operating conditions, data integrity, component specificity, experimental repeatability, and source tracing matching degree. It comprehensively screens for unqualified source spectra, preventing problematic data from being used in pollution source tracing, emission inventory calculation, air quality simulation, and other work, thus fundamentally eliminating deviations in subsequent analysis results.

Description

Technical Field

[0001] This invention relates to the field of atmospheric environmental monitoring technology, specifically to a source spectrum quality evaluation system for organic matter emissions from atmospheric pollution sources. Background Technology

[0002] Volatile organic compounds (VOCs) are key precursors to urban ozone and secondary aerosol pollution. Emission source profiles are crucial foundational data for pollution source tracing, pollution cause analysis, emission reduction effectiveness calculation, and air quality simulation. An emission source profile is a collection of data showing the concentration proportions of various organic components emitted from a particular type of pollution source, the types of characteristic pollutants, and emission patterns. The quality of this source profile data directly determines the accuracy of air pollution analysis, simulation, and governance decisions.

[0003] Currently, the industry's quality verification of organic emission source profiles relies on relatively rudimentary technical methods with numerous shortcomings, failing to meet the demands of precise pollution control. Specific issues include: Currently, routine source spectrum quality checks mostly only check for missing data and whether the format is standardized, performing only superficial formal verification. They do not verify core aspects such as whether sampling conditions are compliant, whether pollutant components conform to industry characteristics, whether multiple sampling data are stable, and whether the source spectrum accurately reflects local pollution realities. Many substandard source spectra with abnormal operating conditions, distorted components, or missing key characteristic pollutants are directly used for pollution analysis and inventory calculations, leading to significant deviations in subsequent work results.

[0004] The production processes in different industries, such as chemical engineering, painting, printing, auto repair, and catering, vary greatly, resulting in significant differences in the composition of organic pollutant emissions. However, current common source spectrum evaluation methods use uniform scoring standards and fixed weights, failing to differentiate between industry-specific characteristics. This easily leads to situations where high-quality, industry-specific source spectra are mistakenly judged as unqualified, while generic source spectra that do not conform to actual operating conditions pass the verification smoothly, resulting in low reliability of evaluation results.

[0005] Traditional evaluation methods can only provide a quality score for the source spectrum, judging whether the data is qualified or unqualified, but cannot accurately identify the specific reasons for data anomalies, such as interference from the sampling environment, errors in the testing instrument, fluctuations in production conditions, or human input errors. Furthermore, there is no corresponding data correction function; unqualified data can only be manually reviewed and corrected by technicians, resulting in a large workload, low efficiency, and unavoidable human error, making it unsuitable for handling the batch verification needs of massive amounts of pollution source spectrum data.

[0006] Currently, source spectrum quality assessment relies heavily on the professional experience of technical personnel, lacking a unified and standardized systematic evaluation process. Inconsistent verification standards and judgment criteria among different personnel lead to significant differences and poor repeatability in the evaluation results. At present, China has not yet established a comprehensive intelligent source spectrum quality assessment system covering the entire process, severely hindering the accurate construction of regional pollution source emission inventories and the advancement of refined pollution source tracing.

[0007] Therefore, based on the above-mentioned technical problems, it is necessary for those skilled in the art to develop a source spectrum quality evaluation system for organic matter emissions from air pollution sources. Summary of the Invention

[0008] The purpose of this invention is to provide a source spectrum quality evaluation system for organic matter emissions from air pollution sources, in order to solve the problems mentioned in the background art.

[0009] To achieve the above objectives, the present invention provides the following technical solution: A technical solution for an air pollution source organic matter emission source spectrum quality assessment system includes, in sequence, a source spectrum data acquisition and preprocessing module, an industry classification and weight adaptive configuration module, a five-dimensional quality comprehensive evaluation module, an anomaly tracing and hierarchical diagnosis module, an intelligent correction and optimization module, and a result output and storage management module. The source spectrum data acquisition and preprocessing module is used to complete the acquisition, cleaning, format unification, and anomaly filtering of pollution source-related data. The industry classification and weight adaptive configuration module is used to achieve intelligent classification of pollution source industries, feature matching, and adaptive allocation of evaluation index weights. The five-dimensional quality comprehensive evaluation module is used to conduct source spectrum quality evaluation from multiple dimensions, comprehensively score, and determine the quality level. The anomaly tracing and hierarchical diagnosis module is used to identify the level of data anomalies, identify the causes of anomalies, and generate diagnostic reports. The intelligent correction and optimization module is used to complete, correct, remove, and re-verify unqualified source spectrum data. The result output and storage management module is used to realize full-process data storage, ledger and report generation, data query and export, and statistical analysis.

[0010] As a preferred technical solution, the source spectrum data acquisition and preprocessing module includes a pollution source basic information acquisition unit, a sampling condition parameter acquisition unit, an organic matter source spectrum core data acquisition unit, a regional benchmark source spectrum data retrieval unit, a raw data cleaning unit, a data missing value marking unit, a data format and dimension unification unit, and an environmental and equipment abnormal data filtering unit. The outputs of the pollution source basic information acquisition unit, the sampling condition parameter acquisition unit, the organic matter source spectrum core data acquisition unit, and the regional benchmark source spectrum data retrieval unit are all connected to the input of the raw data cleaning unit. The raw data cleaning unit is connected in series with the data missing value marking unit, the data format and dimension unification unit, and the environmental and equipment abnormal data filtering unit. The output of the environmental and equipment abnormal data filtering unit serves as the overall output of the source spectrum data acquisition and preprocessing module.

[0011] As a preferred technical solution, the industry classification and weight adaptive configuration module includes a pollution source industry intelligent classification unit, an industry standard emission feature library matching unit, an industry emission feature identification unit, an evaluation index adaptive weight calculation unit, and an industry-specific differentiated weight allocation execution unit. The input end of the pollution source industry intelligent classification unit is connected to the output end of the source spectrum data acquisition and preprocessing module. The pollution source industry intelligent classification unit is connected in series with the industry standard emission feature library matching unit and the industry emission feature identification unit. The output end of the industry emission feature identification unit is connected to the evaluation index adaptive weight calculation unit. The evaluation index adaptive weight calculation unit is connected in series with the industry-specific differentiated weight allocation execution unit. The output end of the industry-specific differentiated weight allocation execution unit serves as the overall output end of the industry classification and weight adaptive configuration module.

[0012] As a preferred technical solution, the five-dimensional quality comprehensive evaluation module includes an operating condition compliance verification evaluation unit, a data integrity statistical evaluation unit, a component specificity comparison evaluation unit, an experimental repeatability analysis evaluation unit, a traceability matching degree verification evaluation unit, a multi-index weighted comprehensive scoring calculation unit, and a source spectrum data quality level determination unit. The input ends of the operating condition compliance verification evaluation unit, data integrity statistical evaluation unit, component specificity comparison evaluation unit, experimental repeatability analysis evaluation unit, and traceability matching degree verification evaluation unit are all connected to the output end of the industry classification and weight adaptive configuration module. The output ends of the above five evaluation units are jointly connected to the multi-index weighted comprehensive scoring calculation unit. The multi-index weighted comprehensive scoring calculation unit is connected in series with the source spectrum data quality level determination unit. The output end of the source spectrum data quality level determination unit serves as the total output end of the five-dimensional quality comprehensive evaluation module.

[0013] As a preferred technical solution, the anomaly tracing and hierarchical diagnosis module includes an anomaly level classification and determination unit, a multi-type anomaly cause accurate identification unit, an anomaly problem summary and statistics unit, and a standardized anomaly diagnosis report generation unit. The input end of the anomaly level classification and determination unit is connected to the output end of the five-dimensional quality comprehensive evaluation module. The anomaly level classification and determination unit is sequentially connected to the multi-type anomaly cause accurate identification unit, the anomaly problem summary and statistics unit, and the standardized anomaly diagnosis report generation unit. The output end of the standardized anomaly diagnosis report generation unit serves as the total output end of the anomaly tracing and hierarchical diagnosis module.

[0014] As a preferred technical solution, the intelligent correction and optimization module includes a data missing intelligent interpolation and completion unit, a source spectrum component deviation correction unit, an abnormal component and invalid data removal unit, a repeated sampling data weighted optimization unit, an operating condition abnormal data marking and invalidation unit, and a corrected data secondary verification and evaluation unit. The input ends of the data missing intelligent interpolation and completion unit, the source spectrum component deviation correction unit, the abnormal component and invalid data removal unit, the repeated sampling data weighted optimization unit, and the operating condition abnormal data marking and invalidation unit are all connected to the output end of the abnormal source tracing and hierarchical diagnosis module. The output ends of the above five optimization units are all connected to the corrected data secondary verification and evaluation unit, and the output end of the corrected data secondary verification and evaluation unit serves as the total output end of the intelligent correction and optimization module.

[0015] As a preferred technical solution, the result output and storage management module includes a full-process data archiving and storage unit, a quality traceability ledger generation unit, a standardized evaluation report automatic generation unit, a batch evaluation task execution unit, a data query and export unit, and an industry source spectrum data statistical analysis unit. The input end of the full-process data archiving and storage unit is connected to the output end of the intelligent correction and optimization module. The full-process data archiving and storage unit is connected in parallel to the quality traceability ledger generation unit, the standardized evaluation report automatic generation unit, the batch evaluation task execution unit, the data query and export unit, and the industry source spectrum data statistical analysis unit. Each unit works together to complete data management and result output.

[0016] Compared with existing technologies, the advantages of this invention are: traditional verification only checks superficial issues such as missing data and format specifications, failing to identify core problems such as abnormal sampling conditions, distorted pollutant composition, missing characteristic substances, and insufficient data stability. This system, relying on a five-dimensional quality comprehensive evaluation module, conducts verification from five dimensions: compliance of operating conditions, data integrity, component specificity, test repeatability, and source matching degree. It comprehensively screens for unqualified source profiles, preventing problematic data from being used in pollution source tracing, emission inventory calculation, air quality simulation, and other work, thus fundamentally eliminating deviations in subsequent analysis results.

[0017] The composition and patterns of organic pollutant emissions vary significantly across different industries, such as chemical, spraying, printing, and catering. Traditional solutions, which use uniform scoring standards and fixed weights, are prone to misjudging high-quality industry source profiles while allowing non-compliant generic source profiles to pass. This system, through an industry classification and weight adaptive configuration module, automatically categorizes industries, matches them to industry emission feature databases, and dynamically allocates differentiated evaluation weights. This ensures that the evaluation rules align with the production processes and emission characteristics of each industry, resulting in more realistic evaluation results and significantly improved reliability.

[0018] Traditional source spectrum evaluation lacks standardized procedures and relies entirely on the professional experience of technical personnel. Inconsistent evaluation standards among different personnel lead to poor reproducibility of results. This system unifies evaluation rules and criteria, ensuring consistent and reproducible evaluation results across different batches and by different operators. This effectively supports the accurate construction of regional pollution source emission inventories and the advancement of refined air pollution source tracing. Attached Figure Description

[0019] Figure 1 This is a schematic diagram of the overall modules of an air pollution source organic matter emission spectrum quality assessment system. Figure 2 This is a schematic diagram of the source spectrum data acquisition and preprocessing module of an atmospheric pollution source organic matter emission source spectrum quality evaluation system. Figure 3 A schematic diagram of the industry classification and weight adaptive configuration module of an air pollution source organic matter emission spectrum quality evaluation system; Figure 4 A schematic diagram of a five-dimensional comprehensive quality evaluation module for an atmospheric pollution source organic matter emission spectrum quality evaluation system; Figure 5 A schematic diagram of an anomaly tracing and hierarchical diagnosis module in an atmospheric pollution source organic matter emission spectrum quality evaluation system; Figure 6 This is a schematic diagram of intelligent correction and optimization for an air pollution source organic matter emission spectrum quality evaluation system. Figure 7 This is a result output and storage management module for an atmospheric pollution source organic matter emission spectrum quality evaluation system.

[0020] In the attached diagram, the following modules are marked: 1. Source spectral data acquisition and preprocessing module; 11. Pollution source basic information acquisition unit; 12. Sampling operating condition parameter acquisition unit; 13. Organic matter source spectrum core data acquisition unit; 14. Regional benchmark source spectrum data retrieval unit; 15. Raw data cleaning unit; 16. Data missing value marking unit; 17. Data format and dimension unification unit; 18. Environmental and equipment abnormal data filtering unit; 2. Industry classification and weight adaptive configuration module; 21. Pollution source industry intelligent classification unit; 22. Industry standard emission feature library matching unit; 23. Industry emission feature identification unit; 24. Evaluation index adaptive weight calculation unit; 25. Industry-specific differentiated weight allocation execution unit; 3. Five-dimensional quality comprehensive evaluation module; 31. Operating condition compliance verification evaluation unit; 32. Data integrity statistical evaluation unit; 33. Component specificity comparison evaluation unit; 34. Test repeatability analysis evaluation unit; 35. Source tracing matching degree verification evaluation. Units: 36. Multi-indicator weighted comprehensive scoring calculation unit; 37. Source spectrum data quality level judgment unit; 4. Anomaly tracing and hierarchical diagnosis module; 41. Anomaly registration and hierarchical judgment unit; 42. Accurate identification of multiple types of anomaly causes unit; 43. Anomaly problem summary and statistics unit; 44. Standardized anomaly diagnosis report generation unit; 5. Intelligent correction and optimization module; 51. Data missing intelligent interpolation and completion unit; 52. Source spectrum component deviation correction unit; 53. Anomaly component and invalid data removal unit; 54. Weighted optimization unit for repeated sampling data; 55. Marking and invalidating abnormal operating condition data unit; 56. Secondary verification and evaluation unit for corrected data; 6. Result output and storage management module; 61. Weighted process data archiving and storage unit; 62. Quality cracking and tracing ledger generation unit; 63. Standardized evaluation report automatic generation unit; 64. Batch evaluation task execution unit; 65. Data query and export unit; 66. Industry source spectrum data statistical analysis unit. Detailed Implementation

[0021] The features and exemplary embodiments of various aspects of the present invention will now be described in detail. To make the objectives, technical solutions, and advantages of the present invention clearer, the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments. For those skilled in the art, the present invention can be practiced without some of these specific details. The following description of the embodiments is merely to provide a better understanding of the present invention by illustrating examples of the invention.

[0022] like Figures 1-7As shown, this invention provides a technical solution for a source spectrum quality evaluation system for organic matter emissions from air pollution sources: It includes a source spectrum data acquisition and preprocessing module 1, an industry classification and weight adaptive configuration module 2, a five-dimensional quality comprehensive evaluation module 3, an anomaly tracing and grading diagnosis module 4, an intelligent correction and optimization module 5, and a result output and storage management module 6, all connected sequentially. The source spectrum data acquisition and preprocessing module 1 is used to complete the acquisition, cleaning, format unification, and anomaly filtering of pollution source-related data. Through multi-dimensional data acquisition and preprocessing, it removes initial environmental and equipment anomaly data, unifies the data format to provide standardized basic data for subsequent evaluation, and avoids the result deviation caused by the direct entry of messy raw data into the evaluation process. The industry classification and weight adaptive configuration module 2 is used to realize intelligent industry classification of pollution sources, feature matching, and adaptive allocation of evaluation index weights, solving the problem of distortion in evaluation results caused by the traditional unified scoring standard not distinguishing industry characteristics. The system addresses the issue of ensuring evaluation rules align with the emission characteristics of different industries. The five-dimensional quality comprehensive evaluation module 3 is used to conduct source spectrum quality evaluation from multiple dimensions, comprehensively score and determine quality levels. Compared to traditional methods that only check surface data issues, it can comprehensively screen for core quality defects, preventing problematic data from flowing into subsequent pollution analysis work at the source. The anomaly tracing and grading diagnosis module 4 identifies data anomaly levels, identifies the causes of anomalies, and generates diagnostic reports, solving the problem that traditional evaluations cannot pinpoint the specific causes of anomalies and providing clear guidance for subsequent data correction. The intelligent correction and optimization module 5 is used to complete, correct, remove, and re-verify unqualified source spectrum data, replacing the traditional manual re-examination and modification method, reducing human error and improving correction efficiency. The result output and storage management module 6 realizes full-process data storage, ledger and report generation, data query and export, and statistical analysis, forming a standardized full-process evaluation record to ensure the reproducibility of evaluation results.

[0023] The source spectrum data acquisition and preprocessing module 1 includes a pollution source basic information acquisition unit 11, a sampling condition parameter acquisition unit 12, an organic matter source spectrum core data acquisition unit 13, a regional benchmark source spectrum data retrieval unit 14, a raw data cleaning unit 15, a data missing value marking unit 16, a data format and dimension unification unit 17, and an environmental and equipment abnormal data filtering unit 18. The outputs of the pollution source basic information acquisition unit 11, the sampling condition parameter acquisition unit 12, the organic matter source spectrum core data acquisition unit 13, and the regional benchmark source spectrum data retrieval unit 14 are all connected to the input of the raw data cleaning unit 15. The raw data cleaning unit 15 is connected in series with the data missing value marking unit 16, the data format and dimension unification unit 17, and the environmental and equipment abnormal data filtering unit 18. The output of the environmental and equipment abnormal data filtering unit 18 serves as the overall output of the source spectrum data acquisition and preprocessing module 1. Through the pollution source basic information acquisition unit 15, the module is preprocessed and preprocessed. Information acquisition unit 11 collects basic information such as industry category and production scale; sampling condition parameter acquisition unit 12 collects operating condition parameters such as production load and running time; organic source spectrum core data acquisition unit 13 collects core data such as emission concentration and proportion of different organic components; regional benchmark source spectrum data retrieval unit 14 automatically matches the corresponding regional benchmark source spectrum data of the same type; all collected data enters the raw data cleaning unit 15 to clean up duplicate and erroneous data; then the missing data is located and marked by the data missing value marking unit 16; then the data format and dimension unification unit 17 converts data from different sources and formats into a unified standardized format; finally, the environmental and equipment abnormal data filtering unit 18 filters out obvious abnormal data caused by sampling environment interference and equipment failure, and outputs standardized preprocessed data to provide a reliable basis for subsequent evaluation stages and avoid primary errors in the raw data from affecting the final evaluation results.

[0024] The industry classification and weight adaptive configuration module 2 includes a pollution source industry intelligent classification unit 21, an industry standard emission feature library matching unit 22, an industry emission feature identification unit 23, an evaluation index adaptive weight calculation unit 24, and an industry-specific differentiated weight allocation execution unit 25. The input of the pollution source industry intelligent classification unit 21 is connected to the output of the source spectrum data acquisition and preprocessing module 1. The pollution source industry intelligent classification unit 21 is sequentially connected in series with the industry standard emission feature library matching unit 22 and the industry emission feature identification unit 23. The output of the industry emission feature identification unit 23 is connected to the evaluation index adaptive weight calculation unit 24. The evaluation index adaptive weight calculation unit 24 is connected in series with the industry-specific differentiated weight allocation execution unit 25. The output of the industry-specific differentiated weight allocation execution unit 25 serves as the industry classification and weight adaptive configuration unit. The overall output of the adaptive configuration module 2; the pollution source industry intelligent classification unit 21 automatically classifies the source spectrum to be evaluated into the corresponding industries of chemical, spraying, printing, auto repair and catering based on the pre-processed basic information; then the industry standard emission feature library matching unit 22 matches the standard emission features of the corresponding industry from the preset feature library; then the industry emission feature identification unit 23 compares and identifies the emission feature differences of the source spectrum to be evaluated; the evaluation index adaptive weight calculation unit 24 automatically calculates the adaptation weights of each evaluation dimension such as operating condition compliance and component specificity based on industry characteristics; finally, the industry-specific differentiated weight allocation execution unit 25 completes the weight allocation, realizing the adaptability evaluation of different industries using differentiated evaluation weights, solving the problem of misjudging high-quality industry-specific source spectra caused by traditional unified fixed weights, and greatly improving the credibility of the evaluation results.

[0025] The five-dimensional quality comprehensive evaluation module 3 includes a working condition compliance verification evaluation unit 31, a data integrity statistical evaluation unit 32, a component specificity comparison evaluation unit 33, a test repeatability analysis evaluation unit 34, a traceability matching degree verification evaluation unit 35, a multi-index weighted comprehensive scoring calculation unit 36, and a source spectrum data quality level determination unit 37. The inputs of the working condition compliance verification evaluation unit 31, data integrity statistical evaluation unit 32, component specificity comparison evaluation unit 33, test repeatability analysis evaluation unit 34, and traceability matching degree verification evaluation unit 35 are all connected to the output of the industry classification and weight adaptive configuration module 2. The outputs of these five evaluation units are all connected to the multi-index weighted comprehensive scoring calculation unit 36. The multi-index weighted comprehensive scoring calculation unit 36 ​​is connected in series with the source spectrum data quality level determination unit 37. The output of the source spectrum data quality level determination unit 37 serves as the overall output of the five-dimensional quality comprehensive evaluation module 3. Output: The operating condition compliance verification and evaluation unit 31 verifies whether the production load and operating conditions during the sampling period meet the sampling specifications; the data integrity statistical evaluation unit 32 statistically analyzes the missing data of mandatory emissions; the component specificity comparison evaluation unit 33 compares the difference in the proportion of characteristic components between the source spectrum under evaluation and the industry benchmark source spectrum; the test repeatability analysis evaluation unit 34 analyzes the degree of deviation of parallel sample test data; and the source tracing matching degree verification evaluation unit 35 verifies the degree of matching between the source spectrum data and the regional emission characteristics. After the five evaluation units complete the single-dimensional evaluation, the multi-index weighted comprehensive scoring calculation unit 36 ​​calculates the comprehensive score by combining the adaptively configured weights. Finally, the source spectrum data quality level determination unit 37 determines the quality level of the source spectrum based on the score, realizing a comprehensive screening from surface data problems to core quality defects, avoiding the direct use of unqualified problem data for pollution analysis and inventory accounting, and eliminating deviations in subsequent work results from the root.

[0026] The anomaly tracing and grading diagnosis module 4 includes an anomaly level grading determination unit 41, a multi-type anomaly cause accurate identification unit 42, an anomaly problem summary and statistics unit 43, and a standardized anomaly diagnosis report generation unit 44. The input of the anomaly level grading determination unit 41 is connected to the output of the five-dimensional quality comprehensive evaluation module 3. The anomaly level grading determination unit 41 is sequentially connected in series with the multi-type anomaly cause accurate identification unit 42, the anomaly problem summary and statistics unit 43, and the standardized anomaly diagnosis report generation unit 44. The output of the standardized anomaly diagnosis report generation unit 44 serves as the overall output of the anomaly tracing and grading diagnosis module 4. Unit 41 classifies anomalies into two levels based on the five-dimensional evaluation results: minor correctable anomalies and serious non-compliance anomalies. Then, the multi-type anomaly cause identification unit 42, combined with the anomaly location in the evaluation process, accurately identifies whether the anomaly is caused by sampling environment interference, testing instrument error, production condition fluctuation, or manual data entry error. Then, the anomaly problem summary and statistics unit 43 organizes all anomaly information. Finally, the standardized anomaly diagnosis report generation unit 44 generates a diagnosis report containing anomaly level, specific cause, and location information. This solves the problem that traditional evaluation can only determine whether it is qualified or not but cannot locate the cause of the anomaly, providing a clear direction for subsequent data correction.

[0027] The intelligent correction and optimization module 5 includes a data missing intelligent interpolation and completion unit 51, a source spectrum component deviation correction unit 52, an abnormal component and invalid data removal unit 53, a repeated sampling data weighted optimization unit 54, an operating condition abnormal data marking and invalidation unit 55, and a corrected data secondary verification and evaluation unit 56. The inputs of the data missing intelligent interpolation and completion unit 51, the source spectrum component deviation correction unit 52, the abnormal component and invalid data removal unit 53, the repeated sampling data weighted optimization unit 54, and the operating condition abnormal data marking and invalidation unit 55 are all connected to the output of the abnormality tracing and grading diagnosis module 4. The outputs of the above five optimization units are all connected to the corrected data secondary verification and evaluation unit 56, and the output of the corrected data secondary verification and evaluation unit 56 serves as the total output of the intelligent correction and optimization module 5. For minor missing anomalies diagnosed, the data missing intelligent... The interpolation completion unit 51 completes the data by combining the regional reference source spectrum; for abnormal component deviations, the source spectrum component deviation correction unit 52 corrects the deviations by combining industry characteristics; for severely distorted abnormal components and invalid data, the abnormal component and invalid data removal unit 53 removes them; for data that has been sampled multiple times, the repeated sampling data weighted optimization unit 56 performs weighted optimization by combining confidence level to obtain the optimal result; for data whose sampling conditions seriously do not meet the requirements, the abnormal data marking and invalidation unit 55 marks it as invalid; after all correction and optimization are completed, the corrected data secondary verification and evaluation unit 56 performs a second verification according to the five-dimensional evaluation standard to ensure that the corrected data meets the quality requirements, replacing the traditional manual verification and modification method, reducing human error, improving processing efficiency, and meeting the batch verification needs of massive pollution source spectrum data.

[0028] The results output and storage management module 6 includes a full-process data archiving and storage unit 61, a quality traceability ledger generation unit 62, a standardized evaluation report automatic generation unit 63, a batch evaluation task execution unit 64, a data query and export unit 65, and an industry source spectrum data statistical analysis unit 66. The input end of the full-process data archiving and storage unit 61 connects to the output end of the intelligent correction and optimization module 5. The full-process data archiving and storage unit 61 is connected in parallel to the quality traceability ledger generation unit 62, the standardized evaluation report automatic generation unit 63, the batch evaluation task execution unit 64, the data query and export unit 65, and the industry source spectrum data statistical analysis unit 66. Each unit collaborates to complete data management and results output. The full-process data archiving and storage unit 61 manages data from the original data collection... The entire process, from final calibration to final data archiving and storage, is streamlined. The quality traceability ledger generation unit 62 automatically generates a quality traceability ledger containing full-process operation information. The standardized evaluation report automatic generation unit 63 automatically generates a quality evaluation report that meets the specifications. The batch evaluation task execution unit 64 supports batch evaluation output of multiple source spectrum data. The data query and export unit 6 supports querying and exporting corresponding source spectrum data by industry, region, and quality level. The industry source spectrum data statistical analysis unit 66 can perform statistical analysis on the source spectrum quality distribution of specific regions and industries. This module forms a unified and standardized systematic evaluation process, ensuring that the evaluation results obtained by different personnel are consistent and reproducible, and can support the accurate construction of regional pollution source emission inventories and the advancement of refined pollution traceability work.

[0029] The working principle and usage process of this invention: After assembling the various components of this solution in sequence, the above implementation methods are followed according to actual needs to complete all working steps.

[0030] The above description is only a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any equivalent substitutions or modifications made by those skilled in the art within the scope of the technology disclosed in the present invention, based on the technical solution and inventive concept of the present invention, should be covered within the scope of protection of the present invention.

Claims

1. A source spectrum quality evaluation system for organic matter emissions from air pollution sources, characterized in that, The system includes a source spectrum data acquisition and preprocessing module (1), an industry classification and weight adaptive configuration module (2), a five-dimensional quality comprehensive evaluation module (3), an anomaly tracing and hierarchical diagnosis module (4), an intelligent correction and optimization module (5), and a result output and storage management module (6), which are connected sequentially. The source spectrum data acquisition and preprocessing module (1) is used to complete the acquisition, cleaning, format unification, and anomaly filtering of pollution source-related data. The industry classification and weight adaptive configuration module (2) is used to realize intelligent classification of pollution source industries, feature matching, and adaptive allocation of evaluation index weights. The five-dimensional quality comprehensive evaluation module (3) is used to conduct source spectrum quality evaluation from multiple dimensions, comprehensively score, and determine the quality level. The anomaly tracing and hierarchical diagnosis module (4) is used to identify the level of data anomalies, identify the causes of anomalies, and generate a diagnostic report. The intelligent correction and optimization module (5) is used to complete, correct, remove, and re-verify unqualified source spectrum data. The result output and storage management module (6) is used to realize full-process data storage, ledger and report generation, data query and export, and statistical analysis.

2. The atmospheric pollution source organic matter emission spectrum quality evaluation system according to claim 1, characterized in that: The source spectrum data acquisition and preprocessing module (1) includes a pollution source basic information acquisition unit (11), a sampling condition parameter acquisition unit (12), an organic matter source spectrum core data acquisition unit (13), a regional benchmark source spectrum data retrieval unit (14), a raw data cleaning unit (15), a data missing value marking unit (16), a data format and dimension unification unit (17), and an environmental and equipment abnormal data filtering unit (18). The outputs of the pollution source basic information acquisition unit (11), the sampling condition parameter acquisition unit (12), the organic matter source spectrum core data acquisition unit (13), and the regional benchmark source spectrum data retrieval unit (14) are all connected to the input of the raw data cleaning unit (15). The raw data cleaning unit (15) is connected in series with the data missing value marking unit (16), the data format and dimension unification unit (17), and the environmental and equipment abnormal data filtering unit (18). The output of the environmental and equipment abnormal data filtering unit (18) serves as the total output of the source spectrum data acquisition and preprocessing module (1).

3. The atmospheric pollution source organic matter emission spectrum quality evaluation system according to claim 2, characterized in that: The industry classification and weight adaptive configuration module (2) includes a pollution source industry intelligent classification unit (21), an industry standard emission feature library matching unit (22), an industry emission feature identification unit (23), an evaluation index adaptive weight calculation unit (24), and an industry-specific differentiated weight allocation execution unit (25). The input end of the pollution source industry intelligent classification unit (21) is connected to the output end of the source spectrum data acquisition and preprocessing module (1). The pollution source industry intelligent classification unit (21) is connected in series with the industry standard emission feature library matching unit (22) and the industry emission feature identification unit (23). The output end of the industry emission feature identification unit (23) is connected to the evaluation index adaptive weight calculation unit (24). The evaluation index adaptive weight calculation unit (24) is connected in series with the industry-specific differentiated weight allocation execution unit (25). The output end of the industry-specific differentiated weight allocation execution unit (25) serves as the total output end of the industry classification and weight adaptive configuration module (2).

4. The atmospheric pollution source organic matter emission spectrum quality evaluation system according to claim 3, characterized in that: The five-dimensional quality comprehensive evaluation module (3) includes a working condition compliance verification evaluation unit (31), a data integrity statistical evaluation unit (32), a component specificity comparison evaluation unit (33), a test repeatability analysis evaluation unit (34), a traceability matching degree verification evaluation unit (35), a multi-index weighted comprehensive scoring calculation unit (36), and a source spectrum data quality level determination unit (37). The input ends of the working condition compliance verification evaluation unit (31), the data integrity statistical evaluation unit (32), the component specificity comparison evaluation unit (33), the test repeatability analysis evaluation unit (34), and the traceability matching degree verification evaluation unit (35) are all connected to the output end of the industry classification and weight adaptive configuration module (2). The output ends of the above five evaluation units are connected to the multi-index weighted comprehensive scoring calculation unit (36). The multi-index weighted comprehensive scoring calculation unit (36) is connected in series with the source spectrum data quality level determination unit (37). The output end of the source spectrum data quality level determination unit (37) serves as the total output end of the five-dimensional quality comprehensive evaluation module (3).

5. The atmospheric pollution source organic matter emission spectrum quality evaluation system according to claim 4, characterized in that: The anomaly tracing and grading diagnosis module (4) includes an anomaly level grading determination unit (41), a multi-type anomaly cause accurate identification unit (42), an anomaly problem summary and statistics unit (43), and a standardized anomaly diagnosis report generation unit (44). The input end of the anomaly level grading determination unit (41) is connected to the output end of the five-dimensional quality comprehensive evaluation module (3). The anomaly level grading determination unit (41) is connected in series with the multi-type anomaly cause accurate identification unit (42), the anomaly problem summary and statistics unit (43), and the standardized anomaly diagnosis report generation unit (44). The output end of the standardized anomaly diagnosis report generation unit (44) serves as the total output end of the anomaly tracing and grading diagnosis module (4).

6. The air pollution source organic matter emission spectrum quality evaluation system according to claim 5, characterized in that: The intelligent correction optimization module (5) includes a data missing intelligent interpolation completion unit (51), a source spectrum component deviation correction unit (52), an abnormal component and invalid data removal unit (53), a repeated sampling data weighted optimization unit (54), an operating condition abnormal data marking and invalidation unit (55), and a corrected data secondary verification and evaluation unit (56). The input ends of the data missing intelligent interpolation completion unit (51), the source spectrum component deviation correction unit (52), the abnormal component and invalid data removal unit (53), the repeated sampling data weighted optimization unit (54), and the operating condition abnormal data marking and invalidation unit (55) are all connected to the output end of the abnormal source tracing and hierarchical diagnosis module (4). The output ends of the above five optimization units are all connected to the corrected data secondary verification and evaluation unit (56). The output end of the corrected data secondary verification and evaluation unit (56) serves as the total output end of the intelligent correction optimization module (5).

7. The atmospheric pollution source organic matter emission spectrum quality evaluation system according to claim 6, characterized in that: The result output and storage management module (6) includes a full-process data archiving and storage unit (61), a quality traceability ledger generation unit (62), a standardized evaluation report automatic generation unit (63), a batch evaluation task execution unit (64), a data query and export unit (65), and an industry source spectrum data statistical analysis unit (66). The input end of the full-process data archiving and storage unit (61) is connected to the output end of the intelligent correction and optimization module (5). The full-process data archiving and storage unit (61) is connected in parallel to the quality traceability ledger generation unit (62), the standardized evaluation report automatic generation unit (63), the batch evaluation task execution unit (64), the data query and export unit (65), and the industry source spectrum data statistical analysis unit (66).

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