An industrial plot environmental performance evaluation method, system and program product

Abstract

This application provides a method, system, and program product for environmental performance assessment of industrial sites. The method involves acquiring statistical data of industrial sites within a target area and corresponding satellite remote sensing data for each industrial site during the target assessment period; calculating the comprehensive environmental performance index for each industrial site based on the statistical data, and determining the remote sensing pollution index for each industrial site based on the satellite remote sensing data; performing a coupled comparison test on the comprehensive environmental performance index and the corresponding remote sensing pollution index for each industrial site to obtain the spatial response deviation coefficient for each industrial site; and determining the control measures for each industrial site based on the spatial response deviation coefficient. This improves the accuracy and comprehensiveness of environmental performance assessment of industrial sites.

Description

Technical Field

[0001] This application relates to the field of environmental monitoring technology, and in particular to a method, system, and program product for environmental performance assessment of industrial sites. Background Technology

[0002] With the deepening of the national "dual carbon" strategy and the continuous improvement of the modern environmental governance system, environmental performance assessment of industrial sites has become an important core link in precise, scientific, and law-based pollution control, which is related to the continuous improvement of regional ecological environment quality and the enhancement of environmental governance efficiency.

[0003] Currently, in carrying out environmental performance rating of industrial sites, ecological and environmental regulatory departments mainly rely on enterprises' pollution source census data, pollution discharge permit implementation reports, and related statistical data such as total industrial output value and tax revenue. They then quantify and score the data according to static indicator weights to complete the environmental performance evaluation of industrial sites.

[0004] However, the quality of statistical data is easily affected by the cooperation of the reporting entities, potentially leading to issues such as subjective omissions, delayed reporting, and objective accounting errors. Furthermore, existing environmental monitoring methods have significant spatial coverage limitations, making it difficult to obtain comprehensive and effective statistical data for environmental performance assessments of industrial sites, further restricting the accuracy of environmental performance assessments and the effectiveness of supervision. For example, due to the limited coverage of fixed monitoring stations and constraints such as construction costs and geographical conditions, it is impossible to cover all scattered industrial sites in a low-cost, high-density manner; and pollutant emissions from non-key polluting units are mostly monitored manually at low frequency, resulting in insufficient monitoring continuity, making it difficult for regulatory authorities to obtain continuous spatial impact data on the surrounding atmosphere, water bodies, soil, and other environmental media.

[0005] More importantly, the existing evaluation system is mainly based on static indicator weights for quantitative scoring. The evaluation method is singular, which leads to the fact that the actual environmental impact of some industrial plots that obtain high performance scores under the static evaluation system may be seriously different from the high performance evaluation results, thus creating a blind spot in off-site environmental supervision.

[0006] Therefore, how to construct an effective method for environmental performance evaluation of industrial sites has become a technical problem that urgently needs to be solved in this field. Summary of the Invention

[0007] This application provides a method, system, and program product for environmental performance assessment of industrial sites, in order to solve the problem of large deviations in environmental performance assessment of industrial sites.

[0008] Firstly, a method for environmental performance assessment of industrial land parcels is provided, including: The process involves acquiring statistical data on industrial plots within the target area during the target evaluation period, as well as corresponding satellite remote sensing data. The statistical data includes information on the pollution discharge and economic attributes of each industrial plot. Based on this statistical data, a comprehensive environmental performance index is calculated for each industrial plot. A remote sensing pollution index is then determined based on the satellite remote sensing data, reflecting the spatial environmental impact corresponding to the actual spatial pollution load of the industrial plot. The comprehensive environmental performance index and the corresponding remote sensing pollution index are coupled and compared to obtain a spatial response deviation coefficient for each industrial plot. This coefficient indicates the degree of matching between the actual spatial pollution load of the industrial plot and the environmental performance calculated based on the statistical data. Finally, the control measures for each industrial plot are determined based on their spatial response deviation coefficients, including routine monitoring or abnormal control measures.

[0009] Understandably, satellite remote sensing data can be used to obtain a remote sensing pollution index reflecting the spatial environmental impact corresponding to the actual spatial pollution load of industrial sites. The spatial response deviation coefficient, derived from the remote sensing pollution index and the comprehensive environmental performance index, can then indicate the degree of matching between the actual spatial pollution load of an industrial site and the environmental performance calculated based on statistical data of the industrial site. This allows for the verification of the comprehensive environmental performance index based on industrial site statistical data, achieving collaborative verification of statistical data evaluation and actual spatial pollution load. Furthermore, since the spatial response deviation coefficient indicates the degree of matching between the actual spatial pollution load of an industrial site and the environmental performance calculated based on statistical data, it is possible to identify industrial sites with potential environmental anomalies based on the spatial response deviation coefficient and adopt different control methods. For example, when the value of the spatial response deviation coefficient between the actual spatial pollution load of an industrial site and the statistical data is large, indicating a low degree of matching in environmental performance, it can be determined that the current industrial site has potential environmental anomalies, thus necessitating abnormal control measures. At this point, there is no need to worry about data loss, distortion, environmental background noise interference, or difficulty in matching the spatial scale of multi-source data due to subjective omissions, late reports, and objective accounting errors caused by differences in the cooperation of the reporting entities. This effectively reduces the rate of regulatory false reports and omissions in complex industrial scenarios and further improves the accuracy and comprehensiveness of environmental performance assessment of industrial sites.

[0010] In one possible implementation of the first aspect mentioned above, the remote sensing pollution index of each industrial plot is determined based on satellite remote sensing observation data within the target area. The remote sensing pollution index reflects the degree of spatial environmental impact corresponding to the actual spatial pollution load of the industrial plot. This includes: extracting the characteristic pollutant concentrations corresponding to the remote sensing assessment area of ​​each industrial plot from the satellite remote sensing observation data based on the geographic coordinate information of each industrial plot, thus obtaining the characteristic pollutant concentrations corresponding to each industrial plot. The remote sensing assessment area includes the industrial plot and the associated buffer space corresponding to the industrial plot. The spatial response net concentration of each industrial plot is obtained by subtracting the environmental background baseline concentration from the characteristic pollutant concentrations corresponding to each industrial plot. The spatial response net concentrations of each industrial plot are then quantified and normalized to calculate the remote sensing pollution index of each industrial plot.

[0011] Understandably, by subtracting the environmental background baseline concentration from the characteristic pollutant concentration corresponding to each industrial plot to obtain the spatial response net concentration of each industrial plot, the interference of environmental background noise such as cross-regional air mass transport and mobile sources on the actual increase in pollution discharge can be automatically eliminated. On this basis, subsequent deep coupling and comparison of the comprehensive environmental performance index and the remote sensing pollution index can eliminate the difficulty of manual screening of distortion of massive statistical data by the auditors, thereby ensuring the objectivity and effectiveness of the generated hierarchical control instructions. In one possible implementation of the first aspect above, the satellite remote sensing observation data includes at least one of the following: tropospheric nitrogen dioxide column concentration data, tropospheric formaldehyde column concentration data, and aerosol optical thickness data; and, based on the geographic coordinate information of each industrial plot, the characteristic pollutant concentration corresponding to the remote sensing assessment area of ​​each industrial plot is extracted from the satellite remote sensing observation data to obtain the characteristic pollutant concentration corresponding to each industrial plot, wherein the remote sensing assessment area includes the industrial plot and the associated buffer space corresponding to the industrial plot, including: constructing a remote sensing assessment area with a set radius centered on the geographic coordinate information of the industrial plot; based on a set cloud cover threshold, the effective remote sensing pixels within the remote sensing assessment area are processed according to the following time-series averaging formula to obtain the characteristic pollutant concentration of the industrial plot, the time-series averaging formula being: ; in, The concentration of characteristic pollutants in industrial sites; The number of valid observation days within the target evaluation period; The characteristic pollutant column concentration for a single pixel on a single day; For masking functions; The set cloud cover threshold.

[0012] Understandably, this can be achieved by introducing a mask function. Cloud cover threshold The coupling determination can filter out observation data with adverse meteorological conditions and low effective pixel quality at the source. On this basis, time-series averaging processing can effectively eliminate the interference of daily observation random noise and local meteorological instantaneous fluctuations on the evaluation results, thereby obtaining a steady-state concentration benchmark that can objectively characterize the average pollution discharge level within the evaluation period, providing reliable input parameters for subsequent background stripping and performance coupling measurement.

[0013] In one possible implementation of the first aspect above, the spatial response net concentration of each industrial plot is obtained by subtracting the environmental background baseline concentration from the characteristic pollutant concentration corresponding to each industrial plot. This includes: sorting the characteristic pollutant concentrations of all valid remote sensing pixels within the remote sensing assessment area of ​​the industrial plot in ascending order of their values; calculating the average of the characteristic pollutant concentrations corresponding to pixels with values ​​below a set quantile threshold, and using the calculation result as the environmental background baseline concentration of the industrial plot; and obtaining the spatial response net concentration of the industrial plot based on the characteristic pollutant concentrations according to the concentration calculation formula, wherein the concentration calculation formula is: ; in, Indicates the concentration of characteristic pollutants in industrial sites. This indicates the baseline concentration of the environmental background of the industrial site. This indicates the net concentration of spatial response of industrial land parcels.

[0014] Understandably, after sorting the characteristic pollutant concentrations of all valid remote sensing pixels within the remote sensing assessment area of ​​an industrial site in ascending order, the average value of the characteristic pollutant concentrations corresponding to pixels with values ​​below a set quantile threshold represents the background environmental conditions of the local area, influenced by factors such as mobile sources, residential pollution, extreme weather conditions, and long-distance air mass transport across regions. Subtracting the background environmental concentration from the original characteristic pollutant concentration yields the spatial response net concentration, reflecting the net contribution of the industrial site to the local incremental concentration. This method overcomes the limitations of relying solely on absolute concentration values ​​for alarms, accurately identifying false anomalies caused by external factors such as interference from adjacent heavy pollution sources and the superposition of traffic mobile sources.

[0015] In one possible implementation of the first aspect mentioned above, the comprehensive environmental performance index and the corresponding remote sensing pollution index corresponding to each industrial site are coupled and compared for verification to obtain the spatial response deviation coefficient of each industrial site, including: obtaining the spatial response deviation coefficient according to the following deviation measurement formula: ; in, This is the spatial response deviation coefficient; The remote sensing pollution index; It is a comprehensive environmental performance index; The preset environmental performance benchmark constant, and It is greater than the maximum value of the comprehensive environmental performance index.

[0016] In one possible implementation of the first aspect mentioned above, the control method for each industrial plot is determined based on the spatial response deviation coefficient of each industrial plot. The control method includes routine supervision or abnormal control, including: if the spatial response deviation coefficient of an industrial plot is greater than or equal to a first abnormal threshold, it is determined that there is a potential environmental hazard in the industrial plot, and abnormal control is implemented on the industrial plot; if the spatial response deviation coefficient of an industrial plot is less than the first abnormal threshold, it is determined that there is no potential environmental hazard in the industrial plot, and routine supervision is implemented on the industrial plot.

[0017] In one possible implementation of the first aspect mentioned above, abnormal control also includes different levels of abnormal supervision. Furthermore, if the spatial response deviation coefficient of an industrial site is greater than or equal to a first abnormal threshold, and the industrial site is determined to have environmental anomalies, abnormal control measures are implemented. This also includes: if the spatial response deviation coefficient of an industrial site is greater than or equal to the first abnormal threshold and less than or equal to a second abnormal threshold, and the industrial site is determined to have moderate fugitive emissions or data distortion hazards, secondary control measures including key supervision alerts are implemented; wherein the second abnormal threshold is greater than the first abnormal threshold; if the spatial response deviation coefficient of an industrial site is greater than the second abnormal threshold, and the industrial site is determined to have fugitive emissions or data distortion hazards, primary control measures including time-limited rectification and downgrading of industrial land performance are implemented. In one possible implementation of the first aspect mentioned above, the comprehensive environmental performance index corresponding to each industrial plot is calculated based on the statistical data of the industrial plots. This includes: calculating various basic performance indicators of the industrial plots based on pollution emission information and economic output information in the industrial plot statistical data. The basic performance indicators include: unit pollutant output value, unit pollutant tax revenue, and unit pollutant land use. The comprehensive environmental performance index of the industrial plots is obtained by comprehensively calculating the various basic performance indicators according to the preset performance evaluation rules.

[0018] In one possible implementation of the first aspect mentioned above, various basic performance indicators of industrial plots are calculated based on pollution emission information and economic output information in industrial plot statistics. These basic performance indicators include: unit pollutant output value, unit pollutant tax revenue, and unit pollutant land use. Specifically, this involves: obtaining the emission equivalent of each pollutant based on its emission amount and corresponding equivalent value in the pollution emission information; summing the emission equivalents of each pollutant according to pollutant category to obtain the atmospheric environmental index for the corresponding air pollutant category, the water environmental index for the corresponding water pollutant category, and the solid waste environmental index for the corresponding solid pollutant category; then weighting and summing the atmospheric environmental index, water environmental index, and solid waste environmental index to obtain the total environmental index; obtaining the total industrial output value, total tax revenue paid by enterprises, and current industrial land area for each industrial plot in the economic output information; calculating the ratio of total industrial output value to the total environmental index to obtain the unit pollutant output value; calculating the ratio of total tax revenue paid by enterprises to the total environmental index to obtain the unit pollutant tax revenue; and calculating the ratio of current industrial land area to the total environmental index to obtain the unit pollutant land use.

[0019] In one possible implementation of the first aspect mentioned above, the comprehensive environmental performance index of the industrial site is obtained by comprehensively calculating various basic performance indicators according to preset performance evaluation rules. This includes: sorting the unit pollutant output value, unit pollutant tax revenue, and unit pollutant land use of all industrial sites within the target area in descending order of their numerical values ​​to obtain unit pollutant output value sequence, unit pollutant tax revenue sequence, and unit pollutant land use sequence; dividing the sorted unit pollutant output value sequence, unit pollutant tax revenue sequence, and unit pollutant land use sequence into first to fourth evaluation level intervals according to preset sample size distribution rules, and assigning tiered quantitative scores to the basic performance indicators in different intervals to obtain the corresponding scores for unit pollutant output value, unit pollutant tax revenue, and unit pollutant land use; and weighting the scores for unit pollutant output value, unit pollutant tax revenue, and unit pollutant land use belonging to the same industrial site according to the following formula to obtain the comprehensive environmental performance index of the industrial site. ; in, This represents the comprehensive environmental performance index. These refer to the weighting coefficients corresponding to the score for unit pollutant output value, the score for unit pollutant tax revenue, and the score for unit pollutant land use, respectively. The score representing the unit pollutant output value This indicates the score for tax revenue per unit of pollutants and This represents the score assigned to a unit of land used for pollutants.

[0020] Secondly, an environmental performance assessment system for industrial sites is provided, comprising: a data acquisition module for acquiring statistical data of industrial sites within a target area and satellite remote sensing observation data corresponding to each industrial site during the target assessment period; wherein, the statistical data of industrial sites includes data characterizing the pollution discharge and economic attributes of the industrial sites; a ground environmental performance accounting module for calculating the comprehensive environmental performance index corresponding to each industrial site based on the statistical data of each industrial site; and a satellite remote sensing response quantification module for determining the remote sensing response of each industrial site based on the satellite remote sensing observation data corresponding to each industrial site. The remote sensing pollution index reflects the spatial environmental impact corresponding to the actual spatial pollution load of the industrial site. The space-ground collaborative management module is used to couple and compare the comprehensive environmental performance index corresponding to the industrial site with the corresponding remote sensing pollution index to obtain the spatial response deviation coefficient of the industrial site. The spatial response deviation coefficient is used to indicate the degree of matching between the actual spatial pollution load of the industrial site and the environmental performance calculated based on the statistical data of the industrial site. It is also used to determine the management and control method for the industrial site based on the spatial response deviation coefficient, which includes routine supervision or abnormal management.

[0021] Thirdly, a computer program product is provided, including a computer program / instruction, which, when executed by a processor, implements an industrial site environmental performance assessment method that fulfills the first aspect and any of the various possible implementations of the first aspect. Attached Figure Description

[0022] To more clearly illustrate the technical solutions in this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0023] Figure 1 A flowchart illustrating an environmental performance assessment method for industrial land parcels, provided as an embodiment of the present invention; Figure 2 A detailed flowchart illustrating the process of obtaining a comprehensive environmental performance index in an environmental performance evaluation method for a corresponding industrial site, as provided in an embodiment of the present invention; Figure 3 A detailed flowchart illustrating the process of obtaining the remote sensing pollution index in an environmental performance assessment method for a corresponding industrial site, provided in an embodiment of the present invention. Figure 4 A detailed flowchart of another method for environmental performance assessment of industrial land provided in an embodiment of the present invention; Figure 5 This is a structural block diagram of an environmental performance assessment system for industrial land parcels provided in an embodiment of the present invention. Detailed Implementation

[0024] To make the objectives, technical solutions, and advantages of this application clearer, the technical solutions of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0025] As shown in the background section, in the process of environmental performance assessment, inconsistent data quality and a single assessment method can limit the accuracy and comprehensiveness of the assessment, thus creating blind spots in off-site environmental supervision.

[0026] Therefore, to address the aforementioned issues, this application proposes a method for environmental performance assessment of industrial sites. This method involves acquiring statistical data on industrial sites within a target area and corresponding satellite remote sensing data for each industrial site during the target assessment period. The statistical data includes data characterizing the pollution discharge and economic attributes of the industrial sites (e.g., pollution discharge information, economic output information, and geographic coordinates). Based on the statistical data for each industrial site, a comprehensive environmental performance index is calculated for each site, and this index is then used to determine the environmental performance index for each industrial site. Satellite remote sensing data is used to determine the remote sensing pollution index of each industrial site. The remote sensing pollution index reflects the degree of spatial environmental impact corresponding to the actual spatial pollution load of the industrial site. The comprehensive environmental performance index corresponding to the industrial site and the corresponding remote sensing pollution index are coupled and compared to obtain the spatial response deviation coefficient of the industrial site. The spatial response deviation coefficient is used to indicate the degree of matching between the actual spatial pollution load of the industrial site and the environmental performance calculated based on the statistical data of the industrial site. Based on the spatial response deviation coefficient of the industrial site, the control method for the industrial site is determined, which includes routine supervision or abnormal control.

[0027] Understandably, satellite remote sensing data can be used to obtain a remote sensing pollution index reflecting the spatial environmental impact corresponding to the actual spatial pollution load of industrial sites. The spatial response deviation coefficient, derived from the remote sensing pollution index and the comprehensive environmental performance index, can then indicate the degree of matching between the actual spatial pollution load of an industrial site and the environmental performance calculated based on statistical data of the industrial site. This allows for the verification of the comprehensive environmental performance index based on industrial site statistical data, achieving collaborative verification of statistical data evaluation and actual spatial pollution load. Furthermore, since the spatial response deviation coefficient indicates the degree of matching between the actual spatial pollution load of an industrial site and the environmental performance calculated based on statistical data, it is possible to identify industrial sites with potential environmental anomalies based on the spatial response deviation coefficient and adopt different control methods. For example, when the value of the spatial response deviation coefficient between the actual spatial pollution load of an industrial site and the statistical data is large, indicating a low degree of matching in environmental performance, it can be determined that the current industrial site has potential environmental anomalies, thus necessitating abnormal control measures.

[0028] Understandably, this environmental performance assessment method for industrial sites breaks away from the limitations of traditional single assessment methods that rely statically and one-sidedly on ground data. It can automatically and multidimensionally identify industrial sites with potential environmental anomalies from massive amounts of heterogeneous data from multiple sources. It eliminates concerns about data loss, distortion, environmental background noise interference, and difficulty in matching the spatial scale of multi-source data due to subjective omissions, late reports, and objective accounting errors caused by differences in the cooperation of reporting entities. It effectively reduces the rate of regulatory false alarms and omissions in complex industrial scenarios, and further improves the accuracy and comprehensiveness of environmental performance assessment for industrial sites.

[0029] Figure 1 According to some embodiments of this application, a schematic diagram of a method for environmental performance assessment of industrial sites is provided. The implementation steps are as follows: S101, Obtain statistical data on industrial land parcels within the target area during the target evaluation period, as well as corresponding satellite remote sensing observation data for each industrial land parcel. The industrial land parcel statistical data includes data characterizing the pollution discharge and economic attributes of the industrial land parcels.

[0030] In some embodiments, industrial land statistics include pollution emission information, economic output information, and geographic coordinate information of the industrial land. For example, the pollution emission information and economic output information of the industrial land include emissions of various conventional and characteristic pollutants, total industrial output value, total tax revenue paid by enterprises, and current industrial land area, etc.

[0031] The main pollutants involved in the pollution emission information are shown in Table 1 below.

[0032] Table 1 In some embodiments, satellite remote sensing data is primarily used to quantify the actual spatial environmental load of the industrial site area. The satellite remote sensing data corresponding to the industrial site includes satellite remote sensing data of the industrial site and surrounding associated areas. The satellite remote sensing data may include at least one of the following: tropospheric nitrogen dioxide column concentration data, tropospheric formaldehyde column concentration data, and aerosol optical thickness data. Specifically, tropospheric nitrogen dioxide column concentration: used to map and verify the nitrogen oxide emission load in the statistical data; aerosol optical thickness: used to map and verify the suspended particulate matter emission load in the statistical data; tropospheric formaldehyde column concentration: since formaldehyde is an intermediate product of most VOCs photochemical reactions in atmospheric chemistry, this indicator is used to indirectly map and verify the actual spatial emission load of VOCs in the statistical data.

[0033] Understandably, satellite remote sensing data can be raw data directly acquired from satellites such as Sentinel-5P, or it can be pre-processed tropospheric trace gas column concentration product data; no specific restrictions are imposed here.

[0034] Furthermore, in some embodiments, to ensure spatial scale consistency when comparing the remote sensing pollution index of each industrial site with the comprehensive environmental performance index, the system also performs coordinate completion. Specifically, for industrial sites lacking standard latitude and longitude information in the statistical data, third-party map interfaces such as map APIs are called, using related text such as company names as search terms to batch obtain and establish the WGS84 coordinate information of the site. Understandably, through this step, the system constructs a precise mapping basis for multi-source heterogeneous data on a micro-geographical scale.

[0035] S102, based on the statistical data of each industrial plot, the comprehensive environmental performance index corresponding to each industrial plot is calculated, and the remote sensing pollution index of each industrial plot is determined based on the satellite remote sensing observation data corresponding to each industrial plot. The remote sensing pollution index reflects the degree of spatial environmental impact corresponding to the actual spatial pollution load of the industrial plot.

[0036] In some embodiments, the comprehensive environmental performance index of an industrial site is obtained through the following methods. Specifically, based on pollution emission information and economic output information from industrial land statistics, various basic performance indicators for industrial land are calculated. These indicators include: unit pollutant output value, unit pollutant tax revenue, and unit pollutant land use. The comprehensive environmental performance index of the industrial land is then calculated based on pre-set performance evaluation rules. The detailed process is detailed below. Figure 2 The description will not be elaborated here.

[0037] In some embodiments, the remote sensing pollution index of industrial sites is obtained in the following manner. Specifically, based on the geographic coordinate information of each industrial site, the concentration of characteristic pollutants corresponding to the remote sensing assessment area of ​​each industrial site is extracted from satellite remote sensing observation data to obtain the characteristic pollutant concentration corresponding to each industrial site. The remote sensing assessment area includes the industrial site and the associated buffer space corresponding to the industrial site. The concentration of characteristic pollutants corresponding to each industrial site is subtracted from the environmental background baseline concentration corresponding to the industrial site to obtain the spatial response net concentration of each industrial site. The spatial response net concentration of each industrial site is then quantified and normalized to calculate the remote sensing pollution index of each industrial site. The specific process can be found below. Figure 3 The description will not be elaborated here.

[0038] S103, the comprehensive environmental performance index and the corresponding remote sensing pollution index for each industrial site are coupled and compared to obtain the spatial response deviation coefficient for each industrial site. The spatial response deviation coefficient indicates the degree of matching between the actual spatial pollution load of the industrial site and the environmental performance calculated based on statistical data of the industrial site. The value of the spatial response deviation coefficient is inversely proportional to the degree of matching.

[0039] Understandably, a comprehensive environmental performance index can be pre-constructed. Pollution index from remote sensing satellites The rigorous logical mapping and collaborative verification relationship between them is used to establish a deviation measurement formula. Based on the pre-constructed deviation measurement formula, the static score calculated based on industrial land statistics and the dynamic sewage discharge response obtained from satellite remote sensing observation data can be nonlinearly coupled to achieve in-depth feature discrimination of abnormal land plots.

[0040] In some embodiments, the remote sensing pollution index and the comprehensive environmental performance index are extracted; the two indicators are then input into the deviation measurement formula, using a preset environmental performance benchmark constant. The difference between the index and the comprehensive environmental performance index is used as the denominator to calculate the spatial response deviation coefficient, which reflects the actual deviation of the pollution discharge. .

[0041] The following formula (1) shows a deviation measurement formula to obtain the spatial response deviation coefficient.

[0042] Formula (1); in, This is the spatial response deviation coefficient; The remote sensing pollution index; It is a comprehensive environmental performance index; The preset environmental performance benchmark constant, and It is greater than the maximum value of the comprehensive environmental performance index, meaning its value is greater than the maximum value that may occur among all industrial plots. value; This reflects the potential for improvement in the current performance level of the industrial site compared to its ideal upper limit. The comprehensive environmental performance index of the site... When the denominator is higher, The smaller the value, the better. At this point, if satellite remote sensing detects a strong pollution response... The final calculated deviation coefficient This will produce an exponential amplification effect. Understandably, the deviation measurement formula internally constructs a nonlinear constraint mechanism. Through this nonlinear measurement formula, the system can greatly improve its numerical sensitivity to the hidden pollution discharge behavior of high-performing enterprises, effectively making up for the limitations of traditional static evaluation systems that are prone to underreporting and false reporting.

[0043] S104. Based on the spatial response deviation coefficient of each industrial plot, the control method for each industrial plot is determined. This control method includes routine supervision or abnormal control. Furthermore, abnormal control includes different levels of abnormal control measures.

[0044] Understandably, different levels of deviation coefficients, combined with the comprehensive environmental performance index, correspond to differentiated control strategies at different levels. The calculated spatial response deviation coefficients are compared and verified with preset graded anomaly thresholds; based on the combination of specific judgment conditions corresponding to the control method, the corresponding control method is determined. Furthermore, when it is determined that anomaly control is required, i.e., there are corresponding environmental anomaly hazards in the industrial site, graded control instructions can be automatically generated.

[0045] In some embodiments, if the spatial response deviation coefficient of an industrial site is less than a first anomaly threshold, it is determined that the actual spatial pollution load of the industrial site matches the environmental performance calculated by its statistical data, indicating that its statistical data is true and valid and there are no hidden pollution anomalies. This confirms that there are no potential environmental anomalies in the industrial site, and routine supervision of the industrial site is carried out. For example, a status confirmation report containing a data verification pass indicator is generated.

[0046] In other embodiments, if the spatial response deviation coefficient of an industrial site is greater than or equal to a first anomaly threshold, it is determined that there is a potential environmental anomaly hazard in the industrial site, and the industrial site is subject to anomaly control.

[0047] Specifically, set a first abnormal threshold. Second abnormal threshold Where the second anomaly threshold is greater than the first anomaly threshold, the data of each industrial plot are substituted into the logical conditions for structured judgment, and a list of anomalies to be verified is generated. If the spatial response deviation coefficient of an industrial plot is greater than or equal to the first anomaly threshold (…), then… And less than or equal to the second abnormal threshold ( In cases where it is determined that an industrial site has a moderate risk of fugitive emissions or data distortion, secondary control measures including key regulatory alerts will be implemented for the industrial site. For example, a secondary control instruction including key regulatory alerts will be generated. If the spatial response deviation coefficient of the industrial site exceeds the second anomaly threshold (…),… In cases where it is determined that an industrial site has potential risks of fugitive emissions or data distortion, a Level 1 control measure is implemented, including rectification within a specified period and downgrading of industrial land performance. For example, a Level 1 control instruction containing such a instruction is generated. Understandably, based on the generated instruction list, the abnormal risk assessment results are pushed to the local ecological and environmental supervision and maintenance terminal to initiate an on-site source tracing verification request, completing a closed-loop non-site supervision process of "discovery-early warning-verification-disposal."

[0048] Understandably, for industrial sites identified as having potential abnormal risks, after generating tiered control instructions, the results of the abnormal risk assessment are pushed to the local ecological and environmental supervision end and the industrial park management end. The Level 1 and Level 2 control instructions contain multiple abnormal site items, and for each abnormal site item, a corresponding abnormal verification information is generated. The abnormal verification information includes at least one of the following: a comparison chart of the site's environmental performance score and remote sensing pollution index, and a spatial response deviation coefficient. The numerical value and the triggered anomaly classification range; this anomaly verification information provides structured data support for off-site supervision, effectively improving the efficiency of collaborative linkage between the discovery of anomaly clues and on-site law enforcement response.

[0049] Understandably, the environmental performance assessment method for industrial sites provided in this application has changed the technical limitations of the traditional regulatory system, which relies solely on static statistical data and struggles to identify concealed pollution discharges. By continuously coupling and comparing remote sensing pollution indices with comprehensive environmental performance indices, it achieves automatic identification of abnormal environmental behaviors such as concealed and unorganized emissions. This effectively reduces the rate of false alarms and missed alarms in complex industrial scenarios, significantly improves the objectivity and scientific nature of environmental performance assessments, and provides solid data support for achieving precise pollution control and differentiated hierarchical management.

[0050] Figure 2 According to some embodiments of this application, a schematic diagram of the process for obtaining a comprehensive environmental performance index in a method for environmental performance assessment of corresponding industrial sites is provided. The specific steps are as follows: S201 calculates various basic performance indicators for industrial sites based on pollution emission information and economic output information from industrial site statistics. These basic performance indicators include: unit pollutant output value, unit pollutant tax revenue, and unit pollutant land use.

[0051] In some embodiments, based on the emission amount and corresponding equivalent value of each pollutant in the pollution emission information, the emission equivalent number of each pollutant is obtained; the emission equivalent numbers of each pollutant are added together according to the pollutant category to obtain the atmospheric environmental index for the corresponding air pollutant category, the water environmental index for the corresponding water pollutant category, and the solid waste environmental index for the corresponding solid pollutant category; the atmospheric environmental index, the water environmental index, and the solid waste environmental index are then weighted and summed to obtain the total environmental index; the total industrial output value, the total tax paid by enterprises, and the current industrial land area of ​​each industrial plot are obtained from the economic output information; the ratio of the total industrial output value to the total environmental index is calculated to obtain the unit pollutant output value; the ratio of the total tax paid by enterprises to the total environmental index is calculated to obtain the unit pollutant tax; and the ratio of the current industrial land area to the total environmental index is calculated to obtain the unit pollutant land use.

[0052] The following section uses the formula to explain the specific process of obtaining the total environmental index. The following formula (2) shows a specific way to calculate each sub-environmental index (atmospheric environmental index, water environmental index, solid waste environmental index). Formula (2); in, For the first The categories of environmental indices include air environmental index, water environmental index and solid waste environmental index; For the first The total number of pollutant types under the environmental index category; For the first The first under the environmental index The amount of pollutants emitted, For the first The first under the environmental index The equivalent value corresponding to each pollutant.

[0053] Formula (3) below shows an expression for obtaining the total environmental index by weighted summation of the atmospheric environmental index, water environmental index and solid waste environmental index.

[0054] Formula (3); in, For the overall environmental index; These are the atmospheric environmental index, the water environmental index, and the solid waste environmental index. , , These are the weighting coefficients for the three factors.

[0055] Understandably, by converting the emissions of various pollutants into environmental indices based on equivalent values ​​and using these indices as a unified environmental load benchmark, the proportional relationships between the total industrial output value of enterprises within an industrial plot, the total tax revenue paid by enterprises, and the current industrial land area and the total environmental index are established, effectively eliminating the limitations of single-dimensional evaluation. This calculation process not only assesses the direct economic output of the plot but also introduces the spatial utilization efficiency of land resources, thereby representing the comprehensive resource output benefits under a unit environmental load in a multidimensional way, laying an objective data foundation for subsequent performance evaluation.

[0056] S202, based on the preset performance evaluation rules, comprehensively calculates various basic performance indicators to obtain the comprehensive environmental performance index of the industrial land plot.

[0057] In some embodiments, the unit pollutant output value, unit pollutant tax revenue, and unit pollutant land use of all industrial plots within the target area are sorted in descending order of numerical value to obtain unit pollutant output value sequence, unit pollutant tax revenue sequence, and unit pollutant land use sequence. Following a preset sample size ratio (e.g., 3:3:3:1), the sorted unit pollutant output value sequence, unit pollutant tax revenue sequence, and unit pollutant land use sequence are divided into first to fourth evaluation level intervals, and tiered quantitative scores are assigned to the basic performance indicators in different intervals (e.g., ...). , , and The quantitative score of pollutant output value, pollutant tax revenue per unit, and pollutant land use per unit are obtained. The comprehensive environmental performance index of the industrial plot is obtained by weighting the pollutant output value per unit, pollutant tax revenue per unit, and pollutant land use per unit belonging to the same industrial plot.

[0058] The following formula (4) shows a formula for calculating the comprehensive environmental performance index.

[0059] Formula (4); in, This represents the comprehensive environmental performance index. These refer to the weighting coefficients corresponding to the score for unit pollutant output value, the score for unit pollutant tax revenue, and the score for unit pollutant land use, respectively. The score representing the unit pollutant output value This represents the score assigned to a unit of pollutant tax revenue. This represents the score assigned to a unit of land used for pollutants.

[0060] Understandably, adopting a sample-ranking-based scoring algorithm, instead of traditional absolute numerical scoring, effectively eliminates the impact of extreme outliers on the overall evaluation scale. This mechanism transforms relative rankings into standardized quantitative scores, allowing the evaluation logic to focus on the relative competitiveness and resource utilization level of land parcels within the same sample across the entire region. This ensures the fairness of the evaluation system across different regions and stages of economic development, and effectively eliminates the limitations of single-dimensional evaluations and the impact of extreme outliers on the overall evaluation scale.

[0061] Figure 3 According to some embodiments of this application, a schematic diagram of a specific process for obtaining a remote sensing pollution index in an environmental performance assessment method for a corresponding industrial site is provided. It is understood that characteristic pollutant concentrations can be extracted by performing time-series averaging based on a set cloud cover threshold. Subsequently, a quantile baseline stripping algorithm is introduced to extract and subtract environmental background noise, obtaining the spatial response net concentration reflecting the actual spatial pollution contribution of the site. Then, a dimensionless remote sensing pollution index is obtained through extreme value normalization. The specific steps are as follows: S301. Based on the geographic coordinates of each industrial plot, the characteristic pollutant concentrations corresponding to the remote sensing assessment areas of each industrial plot are extracted from satellite remote sensing observation data, thus obtaining the characteristic pollutant concentrations corresponding to each industrial plot. The remote sensing assessment area includes the industrial plot and the associated buffer space corresponding to it.

[0062] In some embodiments, a remote sensing assessment area with a set radius is constructed centered on the geographic coordinates of the industrial plot; based on a set cloud cover threshold, the effective remote sensing pixels within the remote sensing assessment area are processed according to the following time-series averaging formula to obtain the concentration of characteristic pollutants. The following formula (5) shows a calculation method for the time-series averaging formula.

[0063] Formula (5); in, The concentration of characteristic pollutants; The number of valid observation days within the target evaluation period; The characteristic pollutant column concentration for a single pixel on a single day; For masking functions; The set cloud cover threshold.

[0064] Understandably, this can be achieved by introducing a mask function. Cloud cover threshold The coupling determination can filter out observation data with adverse meteorological conditions and low effective pixel quality at the source. On this basis, time-series averaging processing can effectively eliminate the interference of daily observation random noise and local meteorological instantaneous fluctuations on the evaluation results, thereby obtaining a steady-state concentration benchmark that can objectively characterize the average pollution discharge level within the evaluation period, providing reliable input parameters for subsequent background stripping and performance coupling measurement.

[0065] S302, the spatial response net concentration of each industrial plot is obtained by subtracting the environmental background baseline concentration of each industrial plot from the characteristic pollutant concentration of each industrial plot.

[0066] Understandably, with the launch of high-resolution multispectral satellites such as Sentinel-5P and Gaofen-5, as well as hyperspectral trace gas detection satellites, satellite remote sensing has been widely used for the inversion of atmospheric pollutants. Columnar concentration data of tropospheric atmospheric pollutants can be obtained through spectral absorption feature inversion. However, since remote sensing data captures the integral concentration of the entire atmosphere, its results are extremely susceptible to combined interference from mobile sources, residential sources, extreme weather conditions, and long-distance transport of air masses across regions, resulting in significant background noise. If raw remote sensing data without noise reduction and baseline stripping is used directly for evaluation, low-emission enterprises located near major transportation hubs or downwind of pollution transport channels are easily misclassified as heavily polluting sources, thus affecting the accuracy and reliability of the evaluation results. Therefore, by integrating physical remote sensing characteristics such as quantile background extraction and cloud cover masking into the identification process, a precise separation relationship between spatial pollution increments and background noise was established.

[0067] In some embodiments, the characteristic pollutant concentrations of all valid remote sensing pixels within the remote sensing assessment area of ​​the industrial site are sorted in ascending order of numerical values; the average value of the characteristic pollutant concentrations corresponding to pixels with values ​​lower than a set quantile threshold is calculated, and the calculation result is used as the environmental background baseline concentration of the industrial site; the environmental background baseline concentration is subtracted from the characteristic pollutant concentration of each pixel to obtain the spatial response net concentration of the industrial site (refer to the concentration calculation formula below), and the spatial response net concentration reflects the local incremental concentration of the net contribution of the industrial site.

[0068] Understandably, after averaging the characteristic pollutant concentrations of all valid remote sensing pixels within the remote sensing assessment area of ​​an industrial site, sorting them in ascending order, and then calculating the average of the characteristic pollutant concentrations corresponding to pixels with values ​​below a set quantile threshold, the resulting average value represents the background environmental baseline of the local area, formed by external factors such as mobile sources, residential sources, extreme weather conditions, and long-distance transport of air masses across regions. For example, when a target industrial site is adjacent to an urban arterial road or highway, the characteristic pollutant concentration above the site is not only affected by the company's own production emissions but also strongly influenced by the superimposed interference of exhaust emissions from dense traffic flow (i.e., traffic mobile sources). The average value of the characteristic pollutant concentrations corresponding to pixels with values ​​below the set quantile threshold extracts the pixels that are unaffected by industry and objectively reflect the basic environmental conditions of the local traffic and residential environment. Calculating the average value yields the background environmental concentration reflecting these background environmental conditions. Subtracting the background environmental concentration from the original characteristic pollutant concentration then yields the spatial response net concentration. This approach overcomes the limitations of relying solely on absolute concentration values ​​for alarms, and can accurately identify false anomalies caused by external factors such as interference from adjacent heavy pollution sources and the superposition of traffic mobile sources.

[0069] The following formula (6) shows an expression for a concentration calculation formula.

[0070] Formula (6); in, Indicates the concentration of characteristic pollutants in industrial sites. This indicates the baseline concentration of the environmental background of the industrial site. This indicates the net concentration of spatial response of industrial land parcels.

[0071] S303 quantifies and normalizes the net spatial response concentration of each industrial site to calculate the remote sensing pollution index of each industrial site.

[0072] In some embodiments, the maximum and minimum values ​​of the net spatial response concentration of all industrial sites assessed in the same batch are obtained, the net spatial response concentration is normalized, and a dimensionless remote sensing pollution index is calculated. .

[0073] For example, the spatial net response increment of all relevant plots within the target area is mapped to a unified evaluation range of 0-100 points, thereby providing a consistent mathematical scale for subsequent space-ground collaborative verification.

[0074] Understandably, by subtracting the environmental background baseline concentration from the characteristic pollutant concentration corresponding to each industrial plot to obtain the spatial response net concentration of each industrial plot, the interference of environmental background noise such as cross-regional air mass transport and mobile sources on the actual increase in pollution discharge can be automatically eliminated. On this basis, subsequent deep coupling and comparison of the comprehensive environmental performance index and the remote sensing pollution index can eliminate the difficulty of manual screening of distortion of massive statistical data by the auditors, thereby ensuring the objectivity and effectiveness of the generated hierarchical control instructions. Figure 4 According to some embodiments of this application, a schematic diagram of another method for environmental performance assessment of industrial sites is shown. The specific process is as follows: K01 obtains statistical data on industrial land parcels and corresponding satellite remote sensing observation data.

[0075] For example, pollution emission information, economic output information, geographic coordinate information, and corresponding satellite remote sensing observation data for a total of 2256 industrial plots were acquired. The pollution emission information includes wastewater discharge, exhaust gas discharge, and solid waste discharge for each industrial plot within the target evaluation period, specifically including: 13 wastewater pollutant factors such as chemical oxygen demand, ammonia nitrogen, total nitrogen, petroleum hydrocarbons, and volatile phenols; 9 exhaust gas pollutant factors such as sulfur dioxide, nitrogen oxides, particulate matter, and volatile organic compounds; and 2 solid waste pollutant factors including general industrial solid waste and hazardous waste. The economic output information includes the sum of the total industrial output value, the sum of tax paid, and the sum of the industrial land area of ​​all enterprises on each industrial plot. The satellite remote sensing observation data includes images of the tropospheric nitrogen dioxide column concentration, tropospheric formaldehyde column concentration, and aerosol optical thickness in the corresponding areas.

[0076] K02 calculates the comprehensive environmental performance index based on statistical data and obtains the remote sensing pollution index based on satellite remote sensing observation data.

[0077] After obtaining the emission amounts and corresponding equivalent values ​​of each air, water, and solid waste pollutant, and dividing them, the emission equivalent number of each pollutant is obtained. The equivalent values ​​of each pollutant are referenced from the "Table of Taxable Pollutants and Equivalent Values" attached to the Environmental Protection Tax Law of the People's Republic of China. The emission equivalent numbers of each pollutant are then added together to obtain the air environment index, water environment index, and solid waste environment index. This embodiment adjusts the weights of the three in accordance with the latest regional policy guidelines. The environmental index of the target industrial plot is calculated by setting it to 35%, 35% and 30% respectively, and then calculated according to the following formula (7). Formula (7); in, Indicates the first air pollutant to the second. Emissions of various air pollutants; This indicates the first air pollutant to the second. Equivalent values ​​for each type of air pollutant; This represents the overall environmental index; Indicates the first water pollutant to the second The amount of water pollutants discharged; This indicates the first water pollutant to the second. Equivalent values ​​of various water pollutants; These represent the discharge volume of general industrial solid waste and the volume of hazardous waste entrusted for treatment and disposal, respectively. This represents the equivalent value of general industrial solid waste and hazardous waste; subsequently, the gross industrial output value is calculated separately. Total tax revenue and current industrial land area With the overall environmental index The ratio corresponds to the unit pollutant output value. Unit pollutant tax and unit pollutant land As a basic performance indicator.

[0078] The total environmental index of the 2256 industrial land parcels was sorted in descending order of value. Based on a sample size distribution rule of 3:3:3:1, the sorted sequence was divided into four evaluation level ranges (A, B, C, and D), and assigned quantitative scores of 100, 75, 50, and 25 respectively, resulting in the corresponding scores for each indicator. , and In this embodiment, the weights of the three are 40%, 40%, and 20% respectively, and the comprehensive environmental performance index is calculated as shown in the following formula (8).

[0079] Formula (8); The final rating of each industrial plot can be determined by ranking them in descending order of their comprehensive environmental performance index and then dividing them according to a certain proportion. To ensure that industrial plots with the same score are grouped into the same level and that the evaluation results are objective and fair, this embodiment makes slight optimizations and adjustments to the original proportions, ultimately determining the level division proportions to be 31%, 29%, 29%, and 11%. This proportion is close to the original 30%, 30%, 30%, and 10% proportions, while also taking into account the standardization of the scheme and the fairness of the results. The final result is 708 Class A industrial plots (comprehensive environmental performance index between 85 and 100), 655 Class B industrial plots (comprehensive environmental performance index between 65 and 80), 652 Class C industrial plots (comprehensive environmental performance index between 45 and 60), and 241 Class D industrial plots (comprehensive environmental performance index less than 40).

[0080] For example, one industrial land parcel selected from each of the above four types is used as an example to illustrate the subsequent comparison and verification process with satellite remote sensing data, so as to better explain the application effect of the environmental performance assessment method based on industrial land parcels.

[0081] Selected plot 1 ( Plot 2 is a Class A plot with high output value and relatively low pollution emissions; Plot 3 is classified as Category B, and all its indicators show good performance; Plot 4 is classified as Category C, indicating poor environmental performance. The land parcel is classified as Category D, and all of its basic performance indicators are in the lowest range.

[0082] Furthermore, this embodiment uses the tropospheric nitrogen dioxide column concentration image acquired by the Sentinel-5P satellite's TROPOMI sensor as an example.

[0083] A remote sensing assessment area was constructed centered on the completed geographical coordinates of the industrial plots, and a cloud cover threshold was set. To remove pixels affected by weather interference, the formula is executed. (i.e., the initial remote sensing observation concentration (i.e., the concentration of characteristic pollutants) is extracted from the above formula (5).

[0084] The remote sensing assessment area where plot 1 is located was measured. The remote sensing assessment area where Plot 2 is located To eliminate interference from mobile sources and background transmission, background baseline quantile extraction logic is executed: effective pixels within the remote sensing assessment area are sorted in ascending order of concentration, and the average value (i.e., pixel mean) corresponding to the characteristic pollutant concentrations of pixels below the 20th percentile threshold is extracted as the environmental background baseline concentration. .

[0085] According to calculations, the area where Plot 1 is located is a high-traffic zone. After deduction, the net spatial response concentration is obtained. The area where Plot 2 is located After deducting, we get .

[0086] Subsequently, all batches of assessed land parcels were extracted. The maximum and minimum values ​​are found using the extreme value normalization formula. Perform quantization mapping.

[0087] Remote sensing pollution index corresponding to plot 1 Plot 2 has a significant increase in localized net sewage discharge, corresponding to Plots 3 and 4 correspond to respectively and .

[0088] K03, by coupling and comparing the comprehensive environmental performance index and the remote sensing pollution index, the spatial response deviation coefficient is calculated.

[0089] In this embodiment, based on the spatial response deviation measurement formula, the comprehensive environmental performance index, representing data obtained from statistical data, is used. The remote sensing pollution index, which represents actual emissions, Perform nonlinear verification.

[0090] Substituting the above two indicators into the spatial response deviation measurement formula (i.e., the above formula (1)) is used for calculation.

[0091] Specifically, in this embodiment, an environmental performance benchmark constant is set. Substitute the data from each plot of land for verification: Plot 1: ; Plot 2: ; Plot 3: ; Plot 4: .

[0092] K04 generates a corresponding hierarchical control instruction when the spatial response deviation coefficient exceeds the preset threshold.

[0093] For example, in order to achieve differentiated and precise hierarchical control of abnormal risks, the system pre-sets a first abnormal threshold for the spatial response deviation coefficient. The value is 1.0, which is the second anomaly threshold. It is 2.5 (of which ).

[0094] The comparison results for each sample are as follows.

[0095] For plot 3, due to its spatial response deviation coefficient The system determines that the actual spatial pollution load of the industrial site matches the environmental performance calculated by its statistical data, indicating that its statistical data is true and valid and there are no hidden pollution anomalies. Then, it generates a status confirmation report containing a data verification pass mark, and the system monitors it routinely.

[0096] For plots 1 and 4, since they meet the conditions... The system determined that these two industrial plots had a moderate risk of fugitive emissions or inaccurate data. Based on this, the system generated a Level II control instruction containing key monitoring prompts. For plot 2, since it meets the conditions This indicates that the surface statistical data for the site shows a medium-to-high performance level, but the actual pollution load on the local space is severe. Based on this, the system determines that the industrial site has potential risks of fugitive emissions or data distortion, and immediately triggers and generates a Level 1 control order that includes a deadline for rectification and a downgrade of the industrial land performance.

[0097] For industrial plots identified as having the aforementioned potential anomalies, such as plot 2, the system generates a tiered control instruction and simultaneously pushes the anomaly assessment results to the local ecological environment supervision department and the industrial park management department. For this specific plot, the system generates corresponding anomaly verification information. This information provides structured evidence support for off-site supervision, effectively improving the efficiency of collaborative action between anomaly detection and on-site enforcement response.

[0098] The above application process fully verifies that the method described in this application can accurately capture hidden pollution sources that do not match the actual situation by comparing environmental performance expectations and spatial responses under complex background interference, thus avoiding the technical problems of data loss, distortion, environmental background noise interference, and difficulty in matching the spatial scale of multi-source data in environmental performance assessment.

[0099] Figure 5 According to some embodiments of this application, an environmental performance assessment system for industrial sites is shown. For example... Figure 5 The environmental performance assessment system for the industrial land plots shown includes: a data acquisition module, a ground environmental performance accounting module, a satellite remote sensing response quantification module, and a satellite-ground collaborative management and control module.

[0100] Specifically, the data acquisition module is used to acquire industrial plot statistics and satellite remote sensing observation data corresponding to each industrial plot within the target area during the target evaluation period; among them, the industrial plot statistics include data characterizing the pollution discharge and economic attributes of the industrial plots.

[0101] The ground environment performance accounting module is used to calculate the comprehensive environmental performance index corresponding to each industrial plot based on the statistical data of the industrial plots.

[0102] The satellite remote sensing response quantification module is used to determine the remote sensing pollution index of each industrial plot based on the satellite remote sensing observation data corresponding to each industrial plot. The remote sensing pollution index reflects the degree of spatial environmental impact corresponding to the actual spatial sewage discharge load of the industrial plot.

[0103] The space-ground collaborative management and control module is used to couple and compare the comprehensive environmental performance index corresponding to the industrial plot with the corresponding remote sensing pollution index to obtain the spatial response deviation coefficient of the industrial plot. The spatial response deviation coefficient is used to indicate the degree of matching between the actual spatial pollution load of the industrial plot and the environmental performance calculated based on the statistical data of the industrial plot. It is also used to determine the management and control method for the industrial plot based on the spatial response deviation coefficient, which includes routine supervision or abnormal management.

[0104] For example, the data acquisition module may include: a geographic coordinate completion unit, an environmental performance data retrieval unit, and a multi-source data preprocessing unit. The geographic coordinate completion unit is used to query industrial sites lacking coordinate information by calling a map API interface with the company name as the search input, and batch-obtaining the corresponding latitude and longitude coordinates to complete and establish the geographic coordinate information of the industrial sites. The environmental performance data retrieval unit is used to obtain economic output information such as the emissions of conventional and characteristic pollutants and the total industrial output value of each industrial site within the target evaluation period. The multi-source data preprocessing unit is used to perform data cleaning and format alignment on the acquired multi-source heterogeneous data.

[0105] For example, the ground environmental performance accounting module further includes: a basic performance indicator calculation unit, a tiered scoring and weighting calculation unit, and an environmental comprehensive index generation unit. The basic performance indicator calculation unit calculates the basic performance indicators. The tiered scoring and weighting calculation unit assigns tiered quantitative scores to the basic performance indicators in different intervals according to preset sample size distribution rules and preset evaluation level interval rules, obtaining the scores for unit pollutant output value, unit pollutant tax revenue, and unit pollutant land use. The environmental comprehensive index generation unit calculates the environmental comprehensive index based on the scores for unit pollutant output value, unit pollutant tax revenue, and unit pollutant land use.

[0106] For example, the satellite remote sensing response quantification module further includes: a remote sensing assessment area construction unit, a cloud cover masking and temporal series unit, a background baseline stripping unit, and a remote sensing pollution index mapping unit. The remote sensing assessment area construction unit is used to determine the remote sensing assessment area. The cloud cover masking and temporal series unit is used to perform temporal averaging on the effective remote sensing pixels within the remote sensing assessment area based on a set cloud cover occlusion threshold, obtaining the characteristic pollutant concentration of the industrial plot. The background baseline stripping unit is used to calculate the average of the characteristic pollutant concentrations corresponding to pixels with values ​​below a set quantile threshold, obtaining the environmental background baseline concentration of the industrial plot. The remote sensing pollution index mapping unit is used to quantify and normalize the spatial response net concentration of each industrial plot, calculating the remote sensing pollution index of each industrial plot.

[0107] For example, the space-ground collaborative control module may further include: a deviation coefficient measurement unit, an intelligent hierarchical decision-making unit, and an instruction generation and distribution unit. The deviation coefficient measurement unit is used to calculate the space response deviation coefficient by calling a nonlinear measurement formula. The intelligent hierarchical decision-making unit is used to compare the deviation coefficient with the set anomaly threshold. , The logical condition determination is performed; the instruction generation and distribution unit is used to automatically generate hierarchical control instructions containing targeted verification information for plots with abnormal potential risks, and push them to the local ecological and environmental supervision terminal.

[0108] This application also provides an electronic device, which includes a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement the industrial land environmental performance assessment method provided in this embodiment.

[0109] This application also provides a computer-readable medium storing instructions that, when executed on a server, cause the server to perform the industrial land environmental performance assessment method mentioned in any of the above embodiments of this application.

[0110] This application also provides a computer program product, including: a computer program / instructions, which, when executed by a processor, implement the industrial site environmental performance assessment method mentioned in any of the above embodiments of this application.

[0111] The above embodiments are only used to illustrate the technical solutions of the present invention and not to limit them. Those skilled in the art should understand that the steps, model formulas, and parameter configurations for performance measurement in the above embodiments are merely examples and can be flexibly adjusted according to the regulatory needs of specific regions in practical applications. Furthermore, the system and its functional modules described in this invention can be executed by a processor as pure software programs or equivalently transformed into hardware entities. Any modifications or equivalent substitutions made to the steps and parameters within the spirit and principles of this invention should be covered within the protection scope of this invention.

Claims

1. An industrial plot environmental performance evaluation method, characterized by, include: Acquire statistical data on industrial land parcels within the target area during the target evaluation period, as well as satellite remote sensing observation data corresponding to each industrial land parcel; wherein, the statistical data on industrial land parcels includes data characterizing the pollution discharge and economic attributes of the industrial land parcels; The comprehensive environmental performance index corresponding to each industrial plot is calculated based on the statistical data of the industrial plots, and the remote sensing pollution index of each industrial plot is determined based on the satellite remote sensing observation data corresponding to each industrial plot. The remote sensing pollution index reflects the degree of spatial environmental impact corresponding to the actual spatial sewage discharge load of the industrial plot. The comprehensive environmental performance index corresponding to each industrial site and the corresponding remote sensing pollution index are coupled and compared to obtain the spatial response deviation coefficient of each industrial site. The spatial response deviation coefficient is used to indicate the degree of matching between the actual spatial pollution load of the industrial site and the environmental performance calculated based on the statistical data of the industrial site. Based on the spatial response deviation coefficient of each industrial plot, the control method for each industrial plot is determined, wherein the control method includes routine supervision or abnormal control.

2. The method of claim 1, wherein, The remote sensing pollution index of each industrial site is determined based on satellite remote sensing observation data corresponding to each industrial site. The remote sensing pollution index reflects the degree of spatial environmental impact corresponding to the actual spatial pollution load of the industrial site, including: Based on the geographic coordinate information of each industrial plot, the concentration of characteristic pollutants corresponding to the remote sensing assessment area of ​​each industrial plot is extracted from the satellite remote sensing observation data to obtain the concentration of characteristic pollutants corresponding to each industrial plot. The remote sensing assessment area includes the industrial plot and the associated buffer space corresponding to the industrial plot. The spatial response net concentration of each industrial site is obtained by subtracting the environmental background baseline concentration from the concentration of the characteristic pollutant corresponding to each industrial site. The spatial response net concentration of each industrial site was quantified and normalized to calculate the remote sensing pollution index of each industrial site.

3. The method according to claim 2, characterized in that, The satellite remote sensing data includes at least one of the following: tropospheric nitrogen dioxide column concentration data, tropospheric formaldehyde column concentration data, and aerosol optical thickness data; Furthermore, based on the geographic coordinate information of each industrial plot, the characteristic pollutant concentration corresponding to the remote sensing assessment area of ​​each industrial plot is extracted from the satellite remote sensing observation data to obtain the characteristic pollutant concentration corresponding to each industrial plot. The remote sensing assessment area includes the industrial plot and the associated buffer space corresponding to the industrial plot, including: A remote sensing assessment area with a set radius is constructed centered on the geographic coordinates of the industrial land parcel; Based on the set cloud cover threshold, the effective remote sensing pixels within the remote sensing assessment area are processed according to the following time-series averaging formula to obtain the characteristic pollutant concentrations of the industrial plots. The time-series averaging formula is as follows: ； wherein, is a concentration of the characteristic pollutant for the industrial plot; is a valid observation day within the target evaluation period; is a single-day single-pixel column concentration of the characteristic pollutant; is a mask function; is a set cloud cover obstruction threshold.

4. The method of claim 2, wherein, The step of subtracting the environmental background baseline concentration from the concentration of the characteristic pollutant corresponding to each industrial plot to obtain the spatial response net concentration of each industrial plot includes: The characteristic pollutant concentrations of all valid remote sensing pixels within the remote sensing assessment area of ​​the industrial site are sorted in ascending order by numerical value. The average concentration of characteristic pollutants corresponding to pixels with values ​​lower than a set quantile threshold is calculated, and the calculation result is used as the environmental background baseline concentration of the industrial site. Based on the environmental background baseline concentration of the industrial site, the spatial response net concentration of the industrial site is obtained by calculating the concentration of characteristic pollutants of the industrial site according to the concentration calculation formula, wherein the concentration calculation formula is: ； wherein, represents the characteristic pollutant concentration of the industrial plot, represents the environmental background baseline concentration of the industrial plot, represents the spatial response net concentration of the industrial plot.

5. The method of claim 1, wherein, The step of coupling and comparing the comprehensive environmental performance index corresponding to each industrial site with the corresponding remote sensing pollution index to obtain the spatial response deviation coefficient of each industrial site includes: The spatial response deviation coefficient of the industrial site is obtained using the following deviation measurement formula: ； in, The spatial response deviation coefficient of the industrial land parcel; The remote sensing pollution index of the industrial site; This refers to the comprehensive environmental performance index of the industrial site. This is a preset environmental performance benchmark constant.

6. The method of claim 1, wherein, The control method for each industrial plot is determined based on its spatial response deviation coefficient. The control method includes routine supervision or abnormal control, including: If the spatial response deviation coefficient of the industrial site is greater than or equal to the first anomaly threshold, it is determined that there is a potential environmental anomaly in the industrial site, and the anomaly control measures are implemented for the industrial site. If the spatial response deviation coefficient of the industrial site is less than the first anomaly threshold, it is determined that there are no environmental anomalies or potential hazards in the industrial site, and the industrial site is subject to routine supervision.

7. The method of claim 6, wherein, The anomaly control also includes different levels of anomaly monitoring, and the step of determining that there is a potential environmental anomaly hazard in the industrial site when the spatial response deviation coefficient of the industrial site is greater than or equal to the first anomaly threshold, and implementing anomaly control for the industrial site, further includes: If the spatial response deviation coefficient of the industrial site is greater than or equal to the first anomaly threshold and less than or equal to the second anomaly threshold, it is determined that the industrial site has a moderate risk of fugitive emissions or data distortion, and the industrial site is subject to secondary control including key regulatory prompts; wherein, the second anomaly threshold is greater than the first anomaly threshold; If the spatial response deviation coefficient of the industrial site is greater than the second anomaly threshold, it is determined that the industrial site has potential risks of unorganized emissions or data distortion, and the industrial site is subject to Level 1 control measures, including time-limited rectification and downgrading of industrial land performance.

8. The method according to any one of claims 1-7, characterized in that, The comprehensive environmental performance index corresponding to each industrial plot is calculated based on the statistical data of the industrial plots corresponding to each industrial plot, including: Based on the pollution emission information and economic output information in the industrial land statistics, the basic performance indicators of the industrial land are calculated. The basic performance indicators include: unit pollutant output value, unit pollutant tax revenue, and unit pollutant land use. The comprehensive environmental performance index of the industrial site is obtained by comprehensively calculating the various basic performance indicators based on the preset performance evaluation rules.

9. The method of claim 8, wherein, The basic performance indicators of the industrial land parcel are calculated based on the pollution emission information and economic output information in the industrial land parcel statistics. These basic performance indicators include: unit pollutant output value, unit pollutant tax revenue, and unit pollutant land use, including: Based on the emission amount and corresponding equivalent value of each pollutant in the pollution emission information, the emission equivalent number of each pollutant is obtained; The emission equivalents of each pollutant are added together according to the pollutant category to obtain the atmospheric environmental index for the corresponding air pollutant category, the water environmental index for the corresponding water pollutant category, and the solid waste environmental index for the corresponding solid pollutant category. The atmospheric environmental index, the water environmental index, and the solid waste environmental index are then weighted and summed to obtain the total environmental index. Obtain the total industrial output value, total tax revenue paid by enterprises, and current industrial land area of ​​each industrial plot from the economic output information; The ratio of the total industrial output value to the total environmental index is calculated to obtain the unit pollutant output value; the ratio of the total tax paid by the enterprise to the total environmental index is calculated to obtain the unit pollutant tax; and the ratio of the current industrial land area to the total environmental index is calculated to obtain the unit pollutant land area.

10. The method of claim 9, wherein, The comprehensive environmental performance index of the industrial site is obtained by comprehensively calculating the various basic performance indicators according to the preset performance evaluation rules, including: The unit pollutant output value, unit pollutant tax revenue, and unit pollutant land use of all industrial plots within the target area are sorted in descending order according to their numerical values ​​to obtain the unit pollutant output value sequence, unit pollutant tax revenue sequence, and unit pollutant land use sequence. According to the preset sample size distribution rules, the sorted unit pollutant output value sequence, unit pollutant tax revenue sequence, and unit pollutant land use sequence are all divided into the first to fourth evaluation level intervals, and the basic performance indicators in different intervals are assigned tiered quantitative scores, which correspond to the assigned scores for the unit pollutant output value, the unit pollutant tax revenue, and the unit pollutant land use. The comprehensive environmental performance index of the industrial plot is obtained by weighting the unit pollutant output value, the unit pollutant tax revenue, and the unit pollutant land use of the same industrial plot according to the following formula: ； in, This represents the comprehensive environmental performance index. These refer to the weighting coefficients corresponding to the assigned score per unit of pollutant output value, the assigned score per unit of pollutant tax revenue, and the assigned score per unit of pollutant land use. The score representing the unit pollutant output value, This indicates the score assigned to the unit pollutant tax revenue and This represents the score assigned to the unit of pollutant land.

11. An industrial plot environmental performance assessment system, characterized by, include: The data acquisition module is used to acquire industrial plot statistics and satellite remote sensing observation data corresponding to each industrial plot within the target area during the target evaluation period; wherein, the industrial plot statistics include data characterizing the pollution discharge and economic attributes of the industrial plots; The ground environment performance accounting module is used to calculate the comprehensive environmental performance index corresponding to each industrial plot based on the statistical data of the industrial plots corresponding to each industrial plot. The satellite remote sensing response quantification module is used to determine the remote sensing pollution index of each industrial plot based on the satellite remote sensing observation data corresponding to each industrial plot. The remote sensing pollution index reflects the degree of spatial environmental impact corresponding to the actual spatial sewage discharge load of the industrial plot. The space-ground collaborative management and control module is used to couple and compare the comprehensive environmental performance index corresponding to the industrial plot with the corresponding remote sensing pollution index to obtain the spatial response deviation coefficient of the industrial plot. The spatial response deviation coefficient is used to indicate the degree of matching between the actual spatial pollution load of the industrial plot and the environmental performance calculated based on the statistical data of the industrial plot. It is also used to determine the management and control method for the industrial plot based on the spatial response deviation coefficient, wherein the management and control method includes routine supervision or abnormal management.

12. A computer program product, characterised in that, It includes a computer program / instruction, which, when executed by a processor, implements the environmental performance assessment method for industrial sites as described in any one of claims 1 to 10.

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