Carbon emission accounting system based on natural water environment pollution source

Abstract

The invention relates to the technical field of carbon emission accounting, in particular to a natural water environment pollution source-based carbon emission accounting system, which comprises a plurality of data acquisition modules, a data processing module, a data accounting module, a database, a data analysis module and an output module. According to the system disclosed by the invention, the collected data is subjected to preprocessing such as accounting, analysis and the like; comparing the calculated carbon emission with a preset threshold to judge a data accounting state; the minimum allowable supplementary value is adjusted based on the judgment result, the standard emission amount and the carbon sink increment are corrected, the minimum distribution interval is further determined according to the adjustment effect, unified processing of carbon emission accounting and optimization of analysis performance are achieved, and the data collection and accounting accuracy and the resource utilization rate of a carbon emission accounting system are effectively improved.

Description

Carbon emission accounting system based on natural water pollution sources Technical Field

[0001] This invention relates to the field of carbon emission accounting technology, and in particular to a carbon emission accounting system based on natural water pollution sources. Background Technology

[0002] The lack of unified standards for carbon emission reduction accounting in water environment management makes it difficult for managers to quickly determine the source of abnormal data, causing significant inconvenience to accounting and maintenance work. This leads to low efficiency in problem investigation, the inability of the system to optimize based on feedback, and difficulty in guaranteeing the reliability and stability of accounting results. To avoid potential risks, quantify the carbon emission reduction benefits of different management measures, and optimize engineering technology routes, higher requirements are placed on the scientific rigor and comparability of accounting results. Numerous professional guidelines have been formulated, filling the gaps in domestic carbon accounting methods. Many stations have begun to choose manual sampling or laboratory analysis, which can promptly detect anomalies and significantly improve overall operational efficiency, becoming a necessary and effective means. Therefore, traditional monitoring and estimation remain one of the important methods of current carbon accounting.

[0003] However, existing accounting models mostly use uniform emission coefficients or simple empirical formulas, failing to consider that carbon emissions in natural aquatic environments are a complex biochemical process involving multiple key parameters such as dissolved oxygen (DO), chemical oxygen demand (COD), chlorophyll a (chl-a), water temperature, and flow rate. Existing technologies are mostly single-point, single-parameter offline sampling or isolated online monitoring, and most devices can only monitor one or a few environmental parameters. Therefore, carbon emission accounting is simplistic and cannot systematically capture the dynamic correlation between various parameters.

[0004] Meanwhile, existing accounting models have many shortcomings. Key parameters involved in the system often rely on empirically set or fixed standard values, lacking real-time monitoring data based on specific regions, and thus failing to form a dynamic adjustment mechanism, which reduces the accuracy of the accounting.

[0005] Chinese Patent Publication No. CN115358698A discloses a carbon emission accounting method based on a data acquisition terminal, including a smart gateway device. The smart gateway device uses a built-in carbon emission accounting formula for calculation, acquires data through real-time monitoring, and sets up a personalized push module to send the acquired data to a unified mobile terminal. The carbon emission result data is obtained based on the energy consumption of the power module.

[0006] Therefore, although the proposed solution can communicate with multiple data acquisition terminals, it still has the following problems: 1. The solution only uses a single intelligent calculation formula for data processing. When the acquired data contains outliers or missing values, it cannot intelligently optimize the intelligent calculation formula, resulting in the inability to effectively collect the carbon emissions corresponding to each region, thus reducing the efficiency of collecting carbon emissions from natural water pollution sources; 2. The solution uses fixed calculation instructions. When the distance between pollution sources changes, there will be delays or deviations in the data calculation, which will affect the working status of subsequent data processing and analysis modules, and further reduce the efficiency of calculating carbon emissions from natural water pollution sources. Summary of the Invention

[0007] To address this issue, the present invention provides a carbon emission accounting system based on natural water environment pollution sources, which overcomes the problem in the prior art where data accounting bias caused by the inability to generate corresponding update instructions based on environmental changes leads to reduced efficiency in carbon emission data accounting for pollution sources in natural water environments.

[0008] To achieve the above objectives, the present invention provides a carbon emission accounting system based on natural water pollution sources, comprising: a data acquisition module, which is set in the area to be accounted for, including a plurality of acquisition device groups for collecting carbon emission data from different carbon emission sources located in various sub-regions within the area; for each acquisition device group located in a single sub-region, the acquisition device group is used to collect carbon emission data of the carbon emission sources in that sub-region, including the type, emission amount, and emission rate of the carbon emission sources; a data processing module, which is connected to each of the acquisition device groups, for preprocessing the carbon emission data, wherein the preprocessing method includes screening, imputation, and standardization of the carbon emission data; wherein, during the data imputation process, a minimum allowable emission supplement value is set for missing values ​​to ensure a minimum difference in carbon emission data; and a data accounting module, which is connected to the data processing module, for determining the carbon emission data based on the carbon emission data preprocessed by the data processing module. The system comprises: a data acquisition module for the region where the data acquisition module is located; a database, which is connected to the data acquisition module, the data processing module, and the calculation module, respectively, for storing the carbon emission data, the preprocessed data, and the comprehensive emission reduction; a data analysis module, which is connected to the calculation module and the database, for determining whether the carbon emission calculation for the region meets the standards based on the comprehensive emission reduction output by the calculation module, and, if it is determined that it does not meet the standards, generating corresponding processing instructions based on the determined reasons, including determining the calculation method of the calculation module for each carbon emission data, or determining the processing method of the data processing module for each carbon emission data; and an output module, which is connected to the data analysis module and the calculation module, for outputting the comprehensive carbon emission obtained by the calculation module if the data analysis module determines that the carbon emission calculation for the region meets the standards.

[0009] Furthermore, the calculation module determines the comprehensive emission reduction (ER) of the area where the data collection module is located based on the contributions of anthropogenic emission reductions and natural carbon sinks. y It can be obtained by the following formula: , among which, BE y This refers to the standard emission level for the area where the data acquisition module is located. PE represents the increase in plant carbon sequestration in the area where the acquisition module is located. y The original emissions (PE) of the area where the acquisition module is located, without carbon sequestration correction. y Calculated using the following formula: , where e i Here, PE is the pollution correction factor for the i-th sub-region, where i = 1, 2, 3, ..., n, and n is the total number of sub-regions in the region. yi For the comprehensive carbon emissions of the i-th sub-region; for the i-th pollution correction coefficient e i ,set up in, Let be the dissolved oxygen concentration in the i-th sub-region. Let be the chemical oxygen demand in the i-th sub-region. Let be the chlorophyll a content in the i-th subregion. This is the dissolved oxygen weighting coefficient. For chemical oxygen weighting coefficient, E0 represents the chlorophyll weighting coefficient and the standard content.

[0010] Furthermore, the data analysis module is used to analyze the comprehensive emission reduction (ER) based on the data. y Compared with the pre-stored comprehensive emission reduction ER in the database y0 The comparison results determine whether the carbon emission accounting for the region complies with the standard, and if it is determined that the carbon emission accounting for the region does not comply with the standard, the reason for non-compliance is determined based on the variance of the emissions of each of the sub-regions.

[0011] Furthermore, the data analysis module is also used to calculate the variance of emissions in each of the sub-regions based on the data accounting module. The pre-stored variance in the database The comparison results determine the reasons for non-compliance with the standards, and, based on the determined reasons, generate corresponding processing methods, including: determining the calculation method of the data accounting module for each carbon emission data when the reason is determined to be an error in the data processing module's data processing, or determining the processing method of the data processing module for each carbon emission data when the reason is determined to be an error in the data accounting module's data accounting.

[0012] Furthermore, the data analysis module is also used to analyze the variance. With the preset variance The difference The minimum allowable emission supplement value is adjusted by the data processing module during the data filling process to increase the minimum allowable emission supplement value, and the increase in the minimum allowable emission supplement value is related to... They are positively correlated.

[0013] Furthermore, the data analysis module is also used to adjust the adjusted minimum allowable emission supplement value according to the supplementary data ratio R to reduce the minimum allowable emission supplement value, and the reduction of the minimum allowable supplement value is negatively correlated with the supplementary data ratio; wherein, the supplementary data ratio R is the ratio of the number of missing data supplemented by the processing module to the total amount of data collected.

[0014] Furthermore, the data analysis module is also used to determine that the reason for non-compliance with the standard is that the data calculation module has an error in the calculation of the data, after optimizing the processing method of the carbon emission data and re-determining that the carbon emission calculation for the region does not meet the standard, and to generate instructions to optimize the calculation method of the actual carbon emission PEy for the region.

[0015] Furthermore, the data analysis module is also used to increase the standard content E0 based on the comparison result between the number of sub-regions n and the preset number N stored in the database, and the increase in the standard content E0 is positively correlated with the number of sub-regions n.

[0016] Furthermore, the data analysis module is also used to reduce the carbon sink increment based on the comparison result between the average distribution distance l and the preset average distribution distance L stored in the database. And the increase in carbon sequestration The decrease in magnitude is negatively correlated with the average distribution distance l; wherein, the average distribution distance is the average of the distribution distances corresponding to each of the acquisition device groups, and for a single distribution distance, it is the distance between the corresponding acquisition device group and the nearest acquisition device group.

[0017] Furthermore, the data analysis module is also used to complete the analysis of the standard content E0 and the increase in plant carbon sequestration. Adjustments and redetering of the overall emission reduction (ER) for the region y If the calculation does not meet the standard, the reason for non-compliance is determined to be an error in the layout of the acquisition module, and instructions are generated to optimize the comprehensive emission reduction for the area. Compared with the prior art, the beneficial effect of the present invention is that, by setting up a data analysis module, the present invention can effectively determine whether there is a collection deviation or calculation deviation in the collection area by analyzing the carbon emission of data in each collection cycle. At the same time, the data analysis module can also output the corresponding processing method according to the determined actual situation, thereby effectively eliminating the deviation caused by abnormal data during the calculation process. While effectively improving the calculation method for different areas, it also effectively avoids the impact of different water qualities on the stability of data transmission, thereby effectively improving the efficiency of carbon emission calculation of the present invention.

[0018] Furthermore, the data processing module of the present invention can achieve data integrity and comparability by filtering out outliers, filling missing values, and standardizing the data. This can transform raw and heterogeneous monitoring data into a highly reliable and standardized high-quality dataset, thereby effectively ensuring the input quality of the subsequent data accounting module and thus effectively improving the accuracy, reliability, and comparability of the final accounting results.

[0019] Furthermore, the data calculation module of this invention calculates the comprehensive emission reduction, actual emission, standard content, and pollution correction coefficient of the area where the acquisition module is located using formulas. This allows for intuitive quantification of the collected data, enabling rapid determination of the actual status of the acquisition process in this cycle. Through the rapidly determined results, the data calculation module can achieve dynamic evaluation of the collected data, thereby effectively outputting corresponding processing decisions. While further improving data calculation for different sub-regions, it also further avoids the impact of the external environment on the stability of data transmission, thus further improving the data calculation efficiency of the solution described in this invention for water pollution sources.

[0020] Furthermore, the data analysis module of the present invention determines whether the data collection for the carbon emission accounting system meets the standards by comparing the obtained comprehensive emission reduction with the preset standard comprehensive emission reduction stored in the database. This makes the standard compliance judgment result more scenario-based and intelligent, effectively avoiding misjudgment and omission of carbon emission accounting by the data analysis module under a single fixed threshold, and further improving the accounting efficiency of the present invention for data in water pollution sources.

[0021] Furthermore, the data analysis module of this invention determines the reasons why the carbon emission calculation does not meet the standards by comparing the variance of the emissions in each sub-region with the pre-stored variances in the database. It can quickly determine whether the variance of carbon emissions within the collection period is qualified. Through the obtained comparison results, the data analysis module can effectively determine the selection of the corresponding processing decision, thereby ensuring that more accurate data can be obtained after updating the processing decision. While further improving the accuracy, it further avoids the occurrence of calculation errors, thereby further improving the calculation efficiency of the data in water pollution sources in the solution of this invention.

[0022] Furthermore, the data analysis module of the present invention determines the minimum allowable emission supplement value for the data processing module during the data filling process by the difference between the variance of the emission of each sub-region and the preset variances pre-stored in the database. This quickly generates an adjustment instruction for the corresponding processing adjustment coefficient of the minimum allowable emission supplement value. By ensuring that the processing adjustment instruction dynamically adjusts the initial minimum allowable emission supplement value, the adjustment multiplier during the data processing process can be adjusted in a targeted manner. This effectively avoids deviations in the data processing process caused by a single fixed threshold being too small. While further improving the completeness of the data processing process, it also accurately determines the range of the minimum allowable emission supplement value, thereby further improving the calculation efficiency of the data in water pollution sources according to the present invention.

[0023] Furthermore, the data analysis module of this invention corrects the adjusted minimum allowable emission supplementary value by supplementing the data ratio. By comparing the supplemented data ratio with the preset ratio stored in the database, it can intuitively determine whether the minimum allowable emission supplementary value meets the standard. At the same time, it stores multiple preset data ratio values, thereby generating a processing correction coefficient for the adjusted minimum allowable emission supplementary value. This further makes the standard compliance judgment result more scenario-based. Thus, by correcting the minimum allowable emission supplementary value with the processing correction coefficient, a more accurate processing result is ensured. While further improving the processing accuracy, it further avoids the occurrence of deviations in the comparison results, thereby further improving the calculation efficiency of the data in water pollution sources in the solution of this invention.

[0024] Furthermore, the data analysis module of this invention optimizes the processing method of the carbon emission data and re-determines the reason why the carbon emission calculation for the region does not meet the standard, which is that the calculation module has an error in the calculation of the data. This invention improves the decision-making efficiency of the system under different collection conditions by repeatedly judging whether the processing of the regional data meets the standard and gradually determining the cause based on the results of repeated judgments. This effectively avoids the system crash caused by over-adjustment of each preset coefficient, further improves the compatibility of carbon emission calculation for different sub-regions, and further improves the calculation efficiency of the solution for data in water pollution sources.

[0025] Furthermore, the data analysis module of the present invention determines the standard content by comparing the number of sub-regions with the preset number stored in the database. Simultaneously, the data analysis module stores multiple preset values. The data accounting module adjusts the standard content by calculating adjustment coefficients, which can intuitively determine whether the number of sub-regions affects the standard content. By calculating adjustment coefficients to corresponding values, a more accurate accounting result is ensured. The data analysis module can dynamically calculate the number of sub-regions under the current circumstances, and further intelligently judge the relationship between excessive, moderate, or insufficient calculation in the current process. This further improves the agility of the data analysis module system while avoiding resource waste, thereby further improving the accounting efficiency of the present invention for data from water pollution sources.

[0026] Furthermore, the data analysis module of the present invention determines the carbon sink increment by comparing the average distribution distance with the preset average distribution distance. Simultaneously, it pre-stores multiple preset values ​​in the data analysis module. The data accounting module adjusts the carbon sink increment by calculating adjustment coefficients, enabling a direct determination of whether the average distribution distance affects the carbon sink increment. By adjusting the carbon sink increment to the corresponding value, a more accurate accounting result is obtained, and corresponding processing decisions are generated, ensuring more accurate data acquisition. This further improves response speed while avoiding deviations in comparison results, thereby further enhancing the accounting efficiency of the present invention for data from water pollution sources.

[0027] Furthermore, the data analysis module of this invention adjusts the standard content and the increase in plant carbon sink, and determines that the reason for non-compliance with the standard calculation for the comprehensive emission reduction of the region is an error in the layout of the acquisition module. This generates corresponding optimization instructions for the comprehensive emission reduction within the sub-region. Based on the comparison between the variance of emissions in each sub-region and the preset variance, the minimum distribution interval of the data acquisition module for the acquisition devices is determined. This effectively avoids data calculation deviations caused by an initially small minimum distribution interval of the acquisition devices. While ensuring the stability of the solution during data calculation, this effectively improves the accuracy of the calculated data, thereby further enhancing the calculation efficiency of the solution for water pollution sources. Attached Figure Description

[0028] Figure 1 is a structural block diagram of the emission accounting system based on natural water pollution sources according to the present invention; Figure 2 is a flowchart of the system of the present invention for determining whether the carbon emission accounting for the region meets the standard based on the comprehensive carbon emission; Figure 3 is an optimized flowchart of the system of the present invention for determining the data processing based on the carbon emission of each sub-region; Figure 4 is an optimized flowchart of the formula calculation of the system of the present invention. Detailed Implementation

[0029] To make the objectives and advantages of the present invention clearer, the present invention will be further described below with reference to embodiments; it should be understood that the specific embodiments described herein are merely for explaining the present invention and are not intended to limit the present invention.

[0030] Preferred embodiments of the present invention will now be described with reference to the accompanying drawings. Those skilled in the art should understand that these embodiments are merely illustrative of the technical principles of the present invention and are not intended to limit the scope of protection of the present invention.

[0031] It should be noted that in the description of this invention, the terms "upper", "lower", "left", "right", "inner", "outer", etc., which indicate directions or positional relationships, are based on the directions or positional relationships shown in the accompanying drawings. This is only for the convenience of description and is not intended to indicate or imply that the device or element must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, it should not be construed as a limitation of this invention.

[0032] Furthermore, it should be noted that, in the description of this invention, unless otherwise explicitly specified and limited, the terms "installation," "connection," and "linking" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection of two components. Those skilled in the art can understand the specific meaning of the above terms in this invention according to the specific circumstances.

[0033] It should be noted that the data in this embodiment are all derived from a comprehensive analysis and evaluation of historical test data and corresponding historical test results from the system described in this invention over the three months prior to this test. Before this test, the system described in this invention comprehensively determines the preset values ​​stored in the database based on the analysis results of 25,863 cumulative tests over the previous three months and the processing results after handling 19,584 specific cases. Those skilled in the art will understand that the system described in this invention can determine the above-mentioned parameters for a single item by selecting the value with the highest proportion based on the data distribution as the preset standard parameter, using weighted summation to obtain the value as the preset standard parameter, substituting each historical data point into a specific formula and using the value obtained by the formula as the preset standard parameter, or other selection methods, as long as the system described in this invention can clearly define different specific situations in the single-item judgment process through the obtained values.

[0034] Please refer to Figure 1, which is a structural block diagram of the emission accounting system based on natural water pollution sources according to the present invention. The carbon emission accounting system based on natural water pollution sources according to the present invention includes several data acquisition modules, data processing modules, data accounting modules, a database, a data analysis module, and an output module. The data acquisition modules are located in the area to be accounted for and include several sets of acquisition devices for collecting data from different carbon emission sources located in various sub-regions within the area. For each set of acquisition devices located in a single sub-region, it collects carbon emission data from the carbon emission sources in that sub-region, including the type, emission amount, and emission rate of the carbon emission sources. The data processing module is connected to each of the acquisition device sets and is used to process the carbon emission data. The process involves preprocessing, including screening, imputation, and standardization of carbon emission data. During data imputation, a minimum allowable emission supplement value is set to ensure minimal discrepancies in carbon emission data for missing values. The data calculation module, connected to the data processing module, determines the comprehensive emission reduction for the region where the acquisition module is located based on the preprocessed carbon emission data. The database, connected to the data acquisition module, data processing module, and calculation module, stores the carbon emission data, the preprocessed data, and the comprehensive emission reduction, respectively. The data analysis module, connected to the calculation module and the database, analyzes the data based on the preprocessed carbon emission data. The calculation module outputs a comprehensive emission reduction to determine whether the carbon emission accounting for the region meets the standards. If the standards are not met, a corresponding processing instruction is generated based on the determined reasons, including determining the calculation method of the data accounting module for each carbon emission data point, or determining the processing method of the data processing module for each carbon emission data point. The output module is connected to the data analysis module and the data accounting module to output the comprehensive carbon emission amount obtained by the accounting module when the data analysis module determines that the carbon emission accounting for the region meets the standards. Specifically, during operation, the system of this invention collects carbon emission data from the corresponding carbon emission sources in the region to be calculated within each cycle of the acquisition device. The system collects emission data and transmits the collected parameters to the data processing module. The data processing module preprocesses the received data and transmits the preprocessed data to the data calculation module. The data calculation module determines the comprehensive carbon emissions of the area where the data collection module is located based on the preprocessed carbon emission data and transmits the calculated data to the database. The data analysis module compares the data obtained by the data calculation module with the carbon emission data stored in the database to determine whether the carbon emission calculation for each sub-area meets the standards. If the calculation does not meet the standards, the module generates corresponding processing instructions based on the determined reasons. The data calculation module or the database performs corresponding operations based on the received instructions.

[0035] Specifically, the data acquisition module includes a pre-installed acquisition device near the mining site, forming an integrated field monitoring unit. Its core components include a water quality parameter sensor group, a hydrological parameter sensor, a meteorological parameter sensor, and a main control and communication unit. The water quality parameter sensor is a submerged device used to collect basic parameters such as temperature, dissolved oxygen, and pH in real time. The hydrological parameter sensor measures the water depth in the drainage ditch to calculate the water area or flow rate. The meteorological parameter sensor corrects the water level and improves calculation accuracy. The main control and communication unit controls each sensor to perform data acquisition, storage, and quality control at a preset frequency. Specifically, the preprocessing methods of the data processing module, including filtering, filling, and standardization, mainly refer to cleaning the raw data into a complete, reliable, high-quality dataset, laying the foundation for subsequent accurate calculations. The data filtering process is... The first part refers to the process of removing data points with obvious errors or unreliability from the dataset. The data processing module automatically filters these data points based on preset, standard-compliant rules. The second part refers to the process of estimating and filling the missing data points left after filtering using a unified method. This includes introducing a minimum allowable emission supplement value. By using the set minimum allowable emission supplement value, the minimum value of various types of values ​​to be filled is constrained, thereby preventing the filled data curve from being too smooth and ensuring that the system retains the data's differences and authenticity during the data filling process. The data processing module intelligently selects the filling strategy based on the duration and pattern of the missing data. The third part refers to the process of converting data from different sources and formats into a unified specification and standard to ensure that the data can be processed and compared consistently within the system. Specifically, the system of this invention stores and manages the collected data and calculation results and builds a continuously updated database.

[0036] Please refer to Figure 2, which is a flowchart of the system of the present invention for determining whether the carbon emissions of each sub-region meet the standards. The process of determining whether the data calculation meets the standards based on the comparison results of the comprehensive emission reduction and the comparison results of the variance of the emissions of each sub-region includes: Specifically, in the embodiments of the present invention, the comprehensive emission reduction is set. , among which, ER y BE represents the overall emission reduction for the area where the acquisition module is located. y This refers to the standard emission level for the area where the data acquisition module is located. PE represents the increase in plant carbon sequestration in the area where the acquisition module is located. y The actual emissions in the area where the collection module is located, and the comprehensive emission reduction. , where e i Here, PE is the pollution correction factor for the i-th sub-region, where i = 1, 2, 3, ..., n, and n is the total number of sub-regions in the region.yi This refers to the actual carbon emissions for the i-th sub-region; specifically, it refers to the i-th pollution correction coefficient e. i ,set up Where Di is the dissolved oxygen concentration in the i-th sub-region, Ci is the chemical oxygen content in the i-th sub-region, hi is the chlorophyll a content in the i-th sub-region, α is the dissolved oxygen weighting coefficient, β is the chemical oxygen weighting coefficient, γ is the chlorophyll weighting coefficient, and E0 is the standard content.

[0037] In this embodiment of the invention, a data analysis module reads preset weighting coefficients from the system configuration data. These coefficients include dissolved oxygen weighting coefficient α = 0.2, chemical oxygen weighting coefficient β = 0.5, chlorophyll weighting coefficient γ = 0.3, and standard content E0 = 100. The standard emission reduction PE is then calculated based on the pollution correction coefficients for each sub-region. y0 .

[0038] It is understandable that in the actual calculation process, chemical oxygen demand (COD) has the greatest impact on emissions, therefore it has the largest weighting coefficient. Dissolved oxygen and chlorophyll content have smaller proportions. Combining historical data, a weighting coefficient of α=0.2 for dissolved oxygen, β=0.5 for COD, and γ=0.3 for chlorophyll is used to obtain more accurate calculation results. It is also understandable that in the actual calculation process, the standard content E0 is the weighted sum of dissolved oxygen, COD, and chlorophyll a content under standard conditions, used as a normalization benchmark factor to correct the coefficient calculation process. Specifically, after the data calculation module completes the calculation of the comprehensive emission reduction, the data analysis module compares the comprehensive emission reduction with the standard emission reduction pre-stored in the database. The data analysis module determines whether the data calculation by the data calculation module conforms to the standard based on the comparison results. In this embodiment, the standard emission reduction... .

[0039] If the overall emission reduction is greater than the standard emission reduction The data analysis module determines that the carbon emission calculation for the region meets the standard; if the comprehensive emission reduction is less than or equal to the standard emission reduction... The data analysis module determines that the carbon emission calculation for the region does not meet the standards, and the data analysis module determines the reason for non-compliance based on the variance of emissions in each sub-region.

[0040] It is understood that the database pre-stores minimum allowable emission reduction thresholds for different types of data. Therefore, the above-mentioned assignment of the standard emission reduction is only a preferred embodiment of the system of the present invention. The present invention does not impose specific restrictions on the value of the preset standard emission reduction, as long as the comparison result between the obtained comprehensive emission reduction and the preset standard emission reduction can directly characterize the analysis of the data analysis module.

[0041] Please refer to Figure 3, which is an optimized flowchart of the data processing of the system of the present invention based on the carbon emissions of each sub-region. The process includes: the data analysis module calculating the variance of the emissions of each sub-region. The pre-stored variance in the database A comparison is performed, and based on the comparison results, it is determined whether the data accounting module's accounting of the data meets the standards. In this embodiment, a preset variance is used. If the variance Less than or equal to the preset variance The data analysis module determines that the data does not meet the standard because the data processing module has errors in processing the data, and generates instructions to optimize the processing method of the carbon emission data used to calculate the actual carbon emissions of each sub-region; if the variance Greater than the preset variance The data analysis module determines that the data does not meet the standard because the calculation module has errors in its calculation of the data, and generates instructions to optimize the calculation method for the actual carbon emissions in the region; specifically, this embodiment of the invention uses the variance... With the preset variance The difference The minimum allowable emission replenishment value is determined for the data processing module during the data imputation process. This minimum allowable emission replenishment value refers to the minimum change that must be met or exceeded to fill a missing data point during the data imputation process. It is not a specific fill value, but rather a lower limit constraint on the fill value. This value is used to guide and constrain the data imputation algorithm of the data processing module. The data processing module will use processing adjustment coefficients K1, K2, and K3 to adjust the initial minimum allowable emission replenishment value P. min To the corresponding value, where the first preset difference Second preset difference , If the difference Greater than the second preset difference stored in the database The data analysis module determines that the initial minimum allowable emission supplement value P, which is pre-stored in the database, should be adjusted using the third processing adjustment coefficient k3. min If the difference Less than or equal to the second preset difference And greater than the first preset difference stored in the database. The data analysis module determines that the initial minimum allowable emission supplement value P should be adjusted using the second processing adjustment coefficient k2. min If the difference Less than or equal to the first preset difference The data analysis module determines that the initial minimum allowable emission supplement value P should be adjusted using the first processing adjustment coefficient k1. min It is understood that the reason why the data analysis module of this invention uses variance calculation to adjust the minimum allowable emission supplement value is that variance can measure the spatial heterogeneity of carbon emissions and is key to preserving the authenticity of the system during the data filling process. The initial effect achieved after adjustment includes: retaining or introducing necessary difference values ​​through variance calculation, thereby counteracting the smoothing effect that the filling process itself may bring, thus effectively eliminating the error caused by data failure in the calculation results of carbon emissions; when the analysis module uses the j-th processing adjustment coefficient kj to adjust the initial minimum allowable emission supplement value P min When j=1, 2, 3, set the minimum allowable emission supplement value after adjustment. .

[0042] After the data processing module completes the adjustment of each minimum allowable emission supplementary value, the data analysis module corrects the adjusted minimum allowable emission supplementary values ​​according to the supplementary data ratio R, where the supplementary data ratio R is the ratio of the number of missing data supplemented by the processing module to the total amount of collected data. It can be understood that the reason why the data analysis module of this invention uses the supplementary data ratio to correct the adjusted minimum allowable emission supplementary values ​​is that, during the adjustment process of the minimum allowable supplementary values, if the minimum allowable supplementary values ​​are not restricted, the adjustment may be too high, thus affecting the continuity of data collection at each point. Therefore, a small correction is needed to ensure that the supplemented data is consistent with the actual collected data. The data analysis module ensures the numerical continuity of the data; it compares the obtained supplementary data percentage with the first preset data percentage and the second preset data percentage stored in the database, and determines the processing correction coefficients m1, m2, and m3 to be used based on the comparison results. In this embodiment, the first preset data percentage R1 = 5%, the second preset data percentage R2 = 15%, and the processing correction coefficients m1 = 0.980, m2 = 0.990, and m3 = 0.997. If the supplementary data percentage R is greater than the second preset data percentage R2 stored in the database, the data analysis module determines to use the third processing correction coefficient m3 to correct the adjusted minimum allowable emission supplementary value P. minIf the supplementary data percentage R is less than or equal to the second preset data percentage R2 and greater than the first preset data percentage R1 stored in the database, the data analysis module determines to use the second processing correction coefficient m2 to correct the adjusted minimum allowable emission supplementary value P. min If the proportion of supplementary data R is less than or equal to the proportion of the first preset data R1, the data analysis module determines to use the first processing correction coefficient m1 to correct the adjusted minimum allowable emission supplementary value P. min '; When the analysis module uses the x-th processing correction factor mx to correct the adjusted minimum allowable emission supplement value P min When x=1, 2, 3, set the revised minimum allowable emission supplement value P. min =P min '×mx.

[0043] It is understood that the reason why the data analysis module of the present invention corrects the adjusted minimum allowable emission supplementary value by supplementing the data ratio is that the supplementary data ratio is a direct quantitative indicator for data uncertainty, used to assess the credibility of the current data. The data analysis module needs to generate corresponding processing decisions based on the data reliability. The effect of the correction includes: preventing over-correction when the data is highly uncertain while ensuring sufficient optimization of the data when the reliability is high, thereby improving the overall credibility of the accounting results. It is understood that the database of the embodiment of the present invention is based on the preset data ratio of monitored carbon emissions, and then compares it with the supplementary data ratio obtained through real-time calculation to achieve accurate assessment and graded response of parameter adjustment status. The higher the supplementary data ratio, the lower the data reliability, the more conservative the correction strategy should be, the smaller the correction range, and the closer the correction coefficient value is to 1. Therefore, it is necessary to select the corresponding processing correction coefficient to ensure that the supplementary data ratio is inversely proportional to the corrected minimum allowable emission supplementary value. Therefore, the processing correction coefficient is inversely proportional to the minimum allowable emission supplementary value.

[0044] Please refer to Figure 4, which is an optimization flowchart of the system of the present invention calculated according to the formula. The data analysis module, after optimizing the processing method of the carbon emission data and re-determining whether the carbon emission calculation for the region does not meet the standards, determines the reason for non-compliance. The process includes: if the carbon emission amount... Greater than the standard emission level The data analysis module determines that the reason for non-compliance with the standard is that the data accounting module has errors in the accounting of the data, and generates instructions to optimize the accounting method for the actual carbon emissions in the region.

[0045] Specifically, in this embodiment of the invention, the data analysis module determines the standard content based on the comparison result between the number of sub-regions n and the preset number N. If the number of sub-regions does not conform to the standard and the corresponding preset number stored in the database, the data analysis module will use an adjustment coefficient. The standard content is adjusted to the corresponding value, wherein the first preset quantity N1=5, the second preset quantity N2=15, and the corresponding accounting adjustment coefficient. It is understood that the reason why the data analysis module of the present invention adjusts the standard content by the number of sub-regions is that the current calculation formula is not applicable to the current actual environment. Adjusting the standard content can improve the compatibility of the data accounting module with the current environment, thereby improving the accounting accuracy. If the number of sub-regions is greater than the second preset number N2 stored in the database, the data analysis module determines to use the third accounting adjustment coefficient. Adjust the standard content E0; if the number of sub-regions is less than or equal to the second preset number N2 and greater than the first preset number N1 stored in the database, the data analysis module determines to use the second accounting adjustment coefficient. Adjust the standard content E0; if the number of sub-regions is less than or equal to the first preset number N1, the data analysis module determines to use the first accounting adjustment coefficient. Adjust the standard content E0; when the analysis module uses the p-th processing to calculate the adjustment coefficient. When adjusting the standard content E0, p=1,2,3, and set the adjusted standard content. .

[0046] It is understood that the database pre-stores a minimum allowed number of different sub-regions. Therefore, the above-mentioned assignment of the preset number of the sub-regions is only a preferred embodiment of the system of the present invention. The present invention does not impose specific restrictions on the value of each preset number, as long as the comparison result between the obtained number of sub-regions and each preset number can directly characterize the data analysis module's analysis of each data.

[0047] Specifically, the data analysis module described in this embodiment of the invention is further used to determine the data carbon sink increment based on the comparison result of the average distribution distance l and the preset average distribution distance L; wherein, the average distribution distance is the average value of the distribution distances corresponding to each of the collection device groups, and for a single distribution distance, it is the distance between the corresponding collection device group and the nearest collection device group.

[0048] It is understood that the average distribution distance refers to the straight-line distance between a single pollution source and its nearest neighbor. After calculating the distribution distances for each pollution source, the average of these distances is calculated and recorded as the average distribution distance. If the average distribution distance does not conform to the preset average distribution distance stored in the database, the data analysis module will use a correction factor. , Correct the carbon sink increment respectively The corresponding values ​​are: the first preset average distribution distance L1 = 0.5 km, the second preset average distribution distance L2 = 2.0 km; the corresponding correction coefficients η1 = 0.997, η2 = 0.998, and η3 = 0.999. It can be understood that the reason the data analysis module of this invention adjusts the carbon sink increment using correction coefficients is that the current calculation formula is not applicable to the current actual environment. Adjusting the carbon sink increment can improve the compatibility of the data accounting module with the current environment, thereby improving the accounting accuracy. If the average distribution distance L1 is greater than the second preset average distribution distance L2 stored in the database, the data analysis module determines to use the third correction coefficient η3 to adjust the carbon sink increment. If the average distribution distance l is less than or equal to the second preset average distribution distance L2 and greater than the first preset average distribution distance L1 stored in the database, the data analysis module determines to use the second correction coefficient η2 to adjust the carbon sink increment. If the average distribution distance l is less than or equal to the first preset average distribution distance L1, the data analysis module determines to use the first correction coefficient η1 to adjust the carbon sink increment. When the processing module uses the q-th processing correction coefficient ηq to correct the carbon sink increment. When q=1,2,3, set the corrected carbon sequestration increment. .

[0049] When the data processing module completes the processing of each carbon sink increment After correcting for the standard content E0, the data analysis module redetermines the comprehensive emission reduction ER for the region. y If the calculation fails to meet the standard, the reason for non-compliance is determined to be an error in the layout of the data acquisition module. An instruction is then generated to optimize the overall emission reduction within the region. The adjustment process includes: Specifically, in this embodiment of the invention, the data analysis module adjusts the emission reduction based on the current emission levels of each sub-region. variance With the preset variance The comparison results determine the distribution adjustment coefficient of the minimum distribution interval h of the data acquisition module for the acquisition device. Wherein, the first preset variance Second preset variance ; corresponding distribution adjustment coefficient If the variance Greater than the second preset variance pre-stored in the database The data analysis module determines to use the third distribution adjustment coefficient. Adjust the minimum distribution interval h of the acquisition device; if the variance Less than or equal to the second preset variance And the variance is greater than the first preset variance stored in the database. The data analysis module determines to use the second distribution adjustment coefficient. Adjust the minimum distribution interval h of the acquisition device; if the variance Less than or equal to the first preset variance The data analysis module determines to use the first distribution adjustment coefficient. Adjust the minimum distribution interval h of the acquisition device; when the analysis module uses the r-th processing distribution adjustment coefficient When adjusting the minimum distribution distance h of the acquisition devices, r=1,2,3, and the adjusted distribution interval of the acquisition devices is set. .

[0050] It is understood that the database pre-stores minimum allowable variance thresholds for different types of parameters. Therefore, the above-mentioned assignment of values ​​to the first preset variance and the second preset variance is only a preferred embodiment of the system described in this invention. This invention does not impose specific restrictions on the values ​​of each preset variance, as long as the comparison result between the obtained variance and each preset variance can directly characterize the data analysis module's analysis of each parameter. It is understood that the larger the variance, the stronger the spatial heterogeneity. Therefore, it is necessary to increase the adjustment coefficient to increase the distribution interval. Thus, the variance is proportional to the adjustment coefficient. This invention does not impose specific restrictions on the values ​​of each preset adjustment coefficient, as long as the minimum distribution interval is obtained by reading the variance.

[0051] The data analysis module is also used to issue an update command to the database when the adjustment of the corresponding minimum distribution interval is completed, and the carbon emission accounting for natural water pollution sources is recalculated based on the adjusted minimum distribution interval and does not meet the standards.

[0052] The technical solution of the present invention has been described above with reference to the preferred embodiments shown in the accompanying drawings. However, it will be readily understood by those skilled in the art that the scope of protection of the present invention is obviously not limited to these specific embodiments. Without departing from the principles of the present invention, those skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical solutions after these changes or substitutions will all fall within the scope of protection of the present invention.

[0053] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A carbon emission accounting system based on natural water pollution sources, characterized in that, include: The data acquisition module is set in the area to be calculated and includes several sets of acquisition devices for collecting data from different carbon emission sources in each sub-area of ​​the area. For the acquisition device set in a single sub-area, it is used to collect carbon emission data of the carbon emission sources in that sub-area, including the type of carbon emission source, emission amount and emission rate. A data processing module, connected to each of the aforementioned acquisition device groups, is used to preprocess the carbon emission data. The preprocessing methods include screening, imputation, and standardization of the carbon emission data. During the data imputation process, a minimum allowable emission supplement value is set to ensure minimal difference in carbon emission data for missing values. A data calculation module, connected to the data processing module, is used to determine the comprehensive emission reduction for the region where the acquisition module is located based on the preprocessed carbon emission data. A database, connected to the data acquisition module, the data processing module, and the calculation module respectively, is used to store the carbon emission data and the preprocessed data respectively. The system includes: data and the comprehensive emission reduction; a data analysis module connected to the accounting module and the database, used to determine whether the carbon emission calculation for the region complies with the standards based on the comprehensive emission reduction output by the accounting module, and, if it is determined that it does not comply with the standards, to generate corresponding processing instructions based on the determined reasons, including determining the calculation method of the accounting module for each carbon emission data, or determining the processing method of the data processing module for each carbon emission data; and an output module connected to the data analysis module and the accounting module, used to output the comprehensive carbon emission obtained by the accounting module if the data analysis module determines that the carbon emission calculation for the region complies with the standards.

2. The carbon emission accounting system based on natural water pollution sources according to claim 1, characterized in that, The calculation module determines the overall emission reduction for the area where the data collection module is located based on anthropogenic emission reductions and natural carbon sink contributions. It can be obtained by the following formula: ,in, This refers to the standard emission level for the area where the data acquisition module is located. The increase in plant carbon sequestration in the area where the data acquisition module is located. This refers to the original emissions of the area where the acquisition module is located, without carbon sequestration correction. Calculated using the following formula: ,in, In order to target the The pollution correction coefficient for the sub-region, i = 1, 2, 3, ..., n, where n is the total number of sub-regions in the region. For the actual carbon emissions of the i-th sub-region; for the i-th Pollution correction factor ,set up ,in, For the first Dissolved oxygen concentration in the sub-region For the first Chemical oxygen demand in the sub-region For the first chlorophyll in subregion The content, This is the dissolved oxygen weighting coefficient. For chemical oxygen weighting coefficient, This is the chlorophyll weighting coefficient. This is the standard content.

3. The carbon emission accounting system based on natural water pollution sources according to claim 2, characterized in that, The data analysis module is used to analyze the overall emission reduction. Compared with the standard comprehensive emission reduction pre-stored in the database The comparison results determine whether the carbon emission accounting for the region complies with the standard, and if it is determined that the carbon emission accounting for the region does not comply with the standard, the reason for non-compliance is determined based on the variance of the emissions of each of the sub-regions.

4. The carbon emission accounting system based on natural water pollution sources according to claim 3, characterized in that, The data analysis module is also used to calculate the variance of emissions for each of the sub-regions based on the data accounting module. The pre-stored variance in the database The comparison results determine the reasons for non-compliance with the standards, and, based on the determined reasons, generate corresponding processing methods, including: determining the calculation method of the data accounting module for each carbon emission data when the reason is determined to be an error in the data processing module's data processing, or determining the processing method of the data processing module for each carbon emission data when the reason is determined to be an error in the data accounting module's data accounting.

5. The carbon emission accounting system based on natural water pollution sources according to claim 4, characterized in that, The data analysis module is also used to analyze the variance. With the preset variance The difference The minimum allowable emission supplement value is adjusted by the data processing module during the data filling process to increase the minimum allowable emission supplement value, and the increase in the minimum allowable emission supplement value is related to... They are positively correlated.

6. The carbon emission accounting system based on natural water pollution sources according to claim 5, characterized in that, The data analysis module is also used to adjust the adjusted minimum allowable emission supplement value according to the supplementary data ratio R to reduce the minimum allowable emission supplement value, and the reduction of the minimum allowable supplement value is negatively correlated with the supplementary data ratio; wherein, the supplementary data ratio R is the ratio of the number of missing data supplemented by the processing module to the total amount of data collected.

7. The carbon emission accounting system based on natural water pollution sources according to claim 5, characterized in that, The data analysis module is also used to determine that the reason for non-compliance with the standard is that the data calculation module has an error in the calculation of the data, and to generate instructions to optimize the calculation method of the actual carbon emissions PEy in the region when the carbon emission calculation for the region is not in compliance with the standard after the optimization of the carbon emission data processing method is completed and the carbon emission calculation for the region is not in compliance with the standard.

8. The carbon emission accounting system based on natural water pollution sources according to claim 7, characterized in that, The data analysis module is also used to increase the standard content E0 based on the comparison result between the number of sub-regions n and the preset number N stored in the database, and the increase in the standard content E0 is positively correlated with the number of sub-regions n.

9. The carbon emission accounting system based on natural water pollution sources according to claim 8, characterized in that, The data analysis module is also used to analyze the average distribution distance of each of the acquisition device groups. Distance from the preset average distribution stored in the database The comparison results reduce the carbon sink increment. And the increase in carbon sequestration The magnitude of the decrease and the average distribution distance The distribution distance is negatively correlated; wherein, the average distribution distance is the average of the distribution distances corresponding to each of the acquisition device groups, and for a single distribution distance, it is the distance between the corresponding acquisition device group and the nearest acquisition device group.

10. The carbon emission accounting system based on natural water pollution sources according to claim 9, characterized in that, The data analysis module is also used to complete the analysis of the standard content E0 and the increase in plant carbon sequestration. Adjustments and redetering of the overall emission reduction (ER) for the region y If the calculation fails to meet the standard, the reason for non-compliance is determined to be an error in the layout of the data acquisition module, and instructions are generated to optimize the comprehensive emission reduction for the region; the data analysis module is also used to calculate the emission reduction based on the emission PE of each sub-region. yi variance The comparison results with the preset standard variances pre-stored in each of the aforementioned databases increase the minimum distribution interval of each of the aforementioned acquisition devices, and the minimum distribution interval is related to the variance. They are positively correlated.

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