Method and system for evaluating pollution reduction and carbon reduction effects of urban waste recovery treatment

Abstract

The invention belongs to the technical field of pollution reduction and carbon reduction, and discloses a method and a system for evaluating pollution reduction and carbon reduction effects of urban waste recovery treatment. The method comprises the following steps: collecting garbage samples in different states at a municipal solid waste recycling treatment point; performing multi-omics analysis on the garbage samples in different states to obtain microbial gene abundance, gene expression quantity and protein abundance; measuring the contents of different pollutants in the garbage samples in different states, and activity data and emission factors in the municipal solid waste recycling process; analyzing a combined toxicity index and a complete-cycle carbon footprint among different pollutants; performing principal component analysis on the variables corresponding to the garbage samples in different states to obtain principal component characteristics; taking the principal component characteristics as input of an index analysis model to obtain a pollution reduction and carbon reduction index value, and performing pollution reduction and carbon reduction evaluation according to the pollution reduction and carbon reduction index value and the principal component characteristics; according to the invention, the pollution-reducing and carbon-reducing effect of municipal solid waste recycling treatment can be visually quantified.

Description

Technical Field

[0001] The present invention relates to the technical field of pollution reduction and carbon reduction, and more specifically, to a method and system for evaluating the pollution reduction and carbon reduction effects of urban waste recycling and treatment. Background Art

[0002] With the acceleration of urbanization, the amount of urban domestic waste continues to grow, which has put pressure on the environment. For example, landfills occupy a large amount of land resources, and pollutants produced by waste incineration pollute the atmosphere, soil and water. At the same time, traditional waste disposal methods are often accompanied by high carbon emissions. In the context of global response to climate change, how to reduce carbon emissions in the waste disposal process has become an important issue.

[0003] The patent application with publication number CN117649132A discloses a method and device for generating pollution reduction and carbon reduction collaborative evaluation results: constructing a pollution reduction and carbon reduction collaborative evaluation index model for a target city; based on the pollution reduction and carbon reduction collaborative evaluation index model, calculating the first target weights of each of multiple evaluation dimensions, and determining the second target weights of each of multiple influencing strategies under each of the evaluation dimensions; calculating the pollution reduction and carbon reduction collaborative efficiency level value of the target city in the target year based on the index scores of each of the multiple influencing strategies under each of the evaluation dimensions in the target year, the first target weights, and the second target weights; calculating the pollution reduction and carbon reduction synergy effect coefficient of the target city in the target year based on the total first pollutant emissions and the first total carbon emissions of the target city in the target year, as well as the total second pollutant emissions and the second total carbon emissions of the target city in the reference year; generating a pollution reduction and carbon reduction collaborative evaluation result for the target city based on the pollution reduction and carbon reduction synergy efficiency level value and the pollution reduction and carbon reduction synergy effect coefficient. This technical solution constructs a pollution reduction and carbon reduction synergy evaluation index model by adopting the hierarchical analysis method, combines multiple evaluation dimensions at different levels and their corresponding different influencing strategies to analyze the results of pollution reduction and carbon reduction synergy. It enriches the types of indicator data, increases the data basis and dimensions for the analysis of pollution reduction and carbon reduction synergy results, and realizes objective monitoring and analysis of the level of pollution reduction and carbon reduction synergy.

[0004] Although the above method can meet most scenarios, research and practical application of the above method and existing technology have found that the above method and existing technology have at least the following defects: From the macro level of the city, there is insufficient reflection of specific indicators in the recycling and treatment of urban domestic waste, which cannot well reflect the actual effect and level of pollution reduction and carbon reduction of urban domestic waste recycling and treatment; when calculating the total amount of pollutant emissions and the total amount of carbon emissions, the main data obtained are the energy consumption values ​​of the target city for multiple statistical energy consumption items, and there is a lack of utilization of the large amount of micro data generated in the recycling and treatment of urban domestic waste, resulting in insufficient comprehensive data support for the evaluation of pollution reduction and carbon reduction of urban domestic waste recycling and treatment.

[0005] In view of this, the present invention proposes an evaluation method and system for the pollution reduction and carbon reduction effect of urban waste recycling and treatment to solve the above problems. Summary of the invention

[0006] In order to overcome the above-mentioned defects of the prior art and to achieve the above-mentioned purpose, the present invention provides the following technical solution: a method for evaluating the pollution reduction and carbon reduction effect of urban waste recycling and treatment, comprising the following steps: Arrange N sampling points at the urban domestic waste recycling and processing points to collect waste samples in different states according to the preset sampling frequency. The waste samples in different states include solid waste samples, liquid waste samples and gaseous waste samples; Multi-omics analysis was performed on garbage samples in different states to obtain microbial gene abundance, gene expression, and protein abundance; Determination of the content of different pollutants in waste samples of different states, as well as activity data and emission factors in the process of municipal solid waste recycling; Analyze the joint toxicity index between different pollutants based on the content of different pollutants, and analyze the full-cycle carbon footprint based on the activity data and emission factors in the urban domestic waste recycling process; The variables corresponding to the garbage samples of different states were standardized, including microbial gene abundance, microbial gene expression, microbial protein abundance, joint toxicity index and full-cycle carbon footprint; principal component analysis was then performed on the standardized variables to obtain the principal component characteristics; The principal component characteristics are used as the input of the index analysis model to obtain the pollution reduction and carbon reduction index values, and the pollution reduction and carbon reduction evaluation is carried out based on the pollution reduction and carbon reduction index values ​​and the principal component characteristics.

[0007] Furthermore, the method of obtaining the principal component characteristics includes: Arrange the standardized variables into a data matrix, where each row represents a garbage sample and each column represents a variable; calculate the covariance matrix of the data matrix; Perform eigenvalue decomposition on the covariance matrix and obtain The eigenvalues ​​corresponding to the garbage samples and the corresponding eigenvector ; Sort the eigenvalues ​​in descending order and select the top eigenvalues ​​based on the cumulative variance contribution rate. The eigenvectors corresponding to the largest eigenvalues ​​form a new matrix ; Based on the new matrix The standardized data matrix Project onto the selected principal component to obtain the reduced-dimensional data matrix ; The reduced data matrix as the principal component features.

[0008] Furthermore, the method of performing eigenvalue decomposition on the covariance matrix includes: For the covariance matrix , calculate the eigenvalue and the corresponding eigenvector, construct and make the eigenvector equation valid; Construct the characteristic equation so that the characteristic vector equation has a non-zero solution; The eigenvalues ​​corresponding to the garbage samples Substitute the eigenvector equation, obtain and solve the homogeneous linear equations corresponding to the eigenvector equation, and get the corresponding eigenvector .

[0009] Furthermore, the training method of the indicator analysis model includes: M groups of garbage sample data are collected in advance, and the garbage sample data include principal component characteristics and corresponding pollution reduction and carbon reduction index values; the principal component characteristics are used as the input of the index analysis model, and the pollution reduction and carbon reduction index values ​​are used as the output of the index analysis model, the index analysis model is trained, and the model parameters of the index analysis model are adjusted based on the gradient descent algorithm to obtain the index analysis model corresponding to the model parameters that minimize the error of the index analysis model as the trained index analysis model.

[0010] Furthermore, the method for evaluating pollution reduction and carbon reduction based on pollution reduction and carbon reduction index values ​​and main component characteristics includes: Calculate the The information entropy of the principal components and the corresponding information entropy weights; then calculate the comprehensive evaluation index .

[0011] Furthermore, the method for obtaining the joint toxicity index between different pollutants includes: Step 1, pre-selecting experimental microorganisms, and conducting a single pollutant toxicity test on each pollutant according to the type of pollutant, obtaining the median lethal concentration of each pollutant for the pre-selected experimental microorganisms, performing equal toxicity ratios for any two different types of pollutants according to the median lethal concentrations, exposing the pre-selected experimental microorganisms to single pollutants of different concentrations, and recording the corresponding mortality rate; exposing the pre-selected experimental microorganisms to pollutant mixtures of different concentrations, recording the corresponding mortality rate, fitting the dose-response curve for the single pollutant or the pollutant mixture based on the probability unit method, and calculating the corresponding median lethal concentration; Step 2: Calculate the toxicity unit of a single pollutant based on the median lethal concentration corresponding to the single pollutant; Step 3: Calculate the total toxicity unit of the mixture based on the toxicity unit of the single pollutant; Step 4: Calculate the combined toxicity index based on the corresponding median lethal concentration of the pollutant mixture and the total toxicity unit of the mixture.

[0012] Further, the method for calculating the median lethal concentration includes: Convert mortality rate to probability units ; Logarithm of pollutant concentration As the independent variable, The value is the dependent variable, and the linear regression fitting is performed to obtain the regression equation, where is the pollutant concentration; the logarithm of the pollutant concentration And the corresponding Substitute the values ​​into the regression equation to solve the fitting parameters and obtain the corresponding regression equation, which is used as the dose-response curve equation; when When the dose-response curve equation is used, the pollutant concentration corresponding to the dose-response curve equation is calculated, and the corresponding pollutant concentration is taken as the corresponding half-lethal concentration.

[0013] Further, methods for obtaining the full-cycle carbon footprint include: Calculate the carbon emissions of the entire cycle to obtain the total carbon emissions, and calculate the carbon footprint of each unit product and per capita in the entire cycle; Methods for obtaining unit product carbon footprint and per capita carbon footprint include: Calculate direct emissions, indirect emissions and other indirect emissions separately; calculate total carbon emissions based on the direct emissions, indirect emissions and other indirect emissions; calculate the carbon footprint per unit product and per capita carbon footprint separately based on the total carbon emissions.

[0014] Furthermore, the method for obtaining the abundance of microbial genes includes: Obtain a known microbial genome database and extract microorganisms from garbage samples in different states; For microorganisms with DNA as genetic material, cell lysis and DNA purification are performed to obtain extracted DNA, and the extracted DNA is subjected to high-throughput sequencing, and the similarity between the DNA sequence data obtained by sequencing and a known microbial genome database is calculated, and the data is compared with a preset DNA similarity threshold. When the similarity is higher than the DNA similarity threshold, the corresponding microbial species in the microbial genome database is used as the type of the extracted microorganism; for microorganisms with RNA as genetic material, cell lysis, RNA separation and reverse transcription are performed to obtain extracted cDNA, and the extracted cDNA is subjected to high-throughput sequencing, and the similarity between the cDNA sequence data obtained by sequencing and a known microbial genome database is calculated, and the data is compared with a preset cDNA similarity threshold. When the similarity is higher than the cDNA similarity threshold, the corresponding microbial species in the microbial genome database is used as the type of the extracted microorganism; According to the type of microorganism, gene prediction is performed on the sequence data based on gene prediction software to obtain the position and sequence of each gene, and the number of reads of each gene in the sequence data is counted. The number of reads represents the number of corresponding genes read from DNA or RNA. The ratio of the number of reads of each gene in the sequence data to the total number of reads of all genes in the sequence data is calculated, and the ratio is used as the gene abundance.

[0015] Furthermore, the method for obtaining the microbial gene expression level includes: The microbial gene expression was calculated by comparing the number of reads of each gene in the sequence data and the total number of reads of all genes in the sequence data in the process of obtaining the microbial gene abundance.

[0016] Further, the method of obtaining the abundance of microbial protein includes: The microorganisms are cultured in a preset culture medium, the microbial cells are ruptured by ultrasonic disruption, the proteins in the cells are extracted, a liquid chromatography system is formed by a liquid chromatography column and a mobile phase, the extracted proteins are injected into the liquid chromatography system, the mobile phase carries the proteins through the liquid chromatography column, the separated protein components flowing out of the liquid chromatography column enter the mass spectrometer, and then ionized to obtain protein ions, the protein ions are separated and detected in the mass analyzer of the mass spectrometer according to the mass-to-charge ratio of the protein ions, the mass spectrometry signal intensity and the total mass spectrometry signal intensity of the protein are obtained, and the ratio of the mass spectrometry signal intensity of the protein to the total mass spectrometry signal intensity is used as the protein abundance.

[0017] An evaluation system for the pollution reduction and carbon reduction effect of urban waste recycling and treatment, which is used to implement an evaluation method for the pollution reduction and carbon reduction effect of urban waste recycling and treatment, comprises: The first collection module: arrange N sampling points at the urban domestic waste recycling and processing points, and collect garbage samples in different states according to the preset sampling frequency. The garbage samples in different states include solid garbage samples, liquid garbage samples and gaseous garbage samples; Multi-omics analysis module: Multi-omics analysis of garbage samples in different states to obtain microbial gene abundance, gene expression and protein abundance; The second collection module: Determine the content of different pollutants in garbage samples of different states, as well as the activity data and emission factors in the process of urban domestic waste recycling and treatment; Data analysis module: Analyze the joint toxicity index of different pollutants based on the content of different pollutants, and analyze the full-cycle carbon footprint based on the activity data and emission factors in the process of urban domestic waste recycling and treatment; Principal component extraction module: Standardize the variables corresponding to the garbage samples in different states, including microbial gene abundance, microbial gene expression, microbial protein abundance, joint toxicity index and full-cycle carbon footprint; then perform principal component analysis on the standardized variables to obtain the principal component characteristics; Comprehensive evaluation module: The principal component characteristics are used as the input of the index analysis model to obtain the pollution reduction and carbon reduction index values, and pollution reduction and carbon reduction evaluation is performed based on the pollution reduction and carbon reduction index values ​​and the principal component characteristics.

[0018] Technical effects and advantages of the method and system for evaluating the pollution reduction and carbon reduction effect of urban waste recycling and treatment of the present invention: The present invention can obtain multi-dimensional garbage data by collecting samples in different states of solid, liquid and gas, comprehensively covering all forms of garbage, ensuring the integrity and representativeness of the data, and laying a solid foundation for subsequent analysis; by performing multi-omics analysis on garbage samples, unique indicators such as microbial gene abundance, gene expression and protein abundance are obtained to reflect the impact of microbial activity on pollution reduction and carbon reduction during garbage treatment; at the same time, based on the analysis of the pollutant content combined with the toxicity index, the full-cycle carbon footprint is analyzed based on activity data and emission factors, covering various information such as energy consumption and material use, and further enriching the evaluation dimensions from the perspective of toxicity and carbon emissions, so as to more accurately reflect the actual situation of pollution reduction and carbon reduction in urban domestic waste recycling and treatment, and provide a reliable basis for relevant decision-making; through standardization and principal component analysis, the influence of data dimensions is effectively eliminated, key features are extracted, and data complexity is simplified. The principal component features are input into the index analysis model to obtain the pollution reduction and carbon reduction index value, which can intuitively quantify the pollution reduction and carbon reduction effect of urban domestic waste recycling and treatment, provide accurate data support for optimizing treatment processes and formulating scientific policies, and help cities achieve green and sustainable development. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1It is a schematic flow chart of the method for evaluating the pollution reduction and carbon reduction effect of urban waste recycling and treatment of the present invention; Figure 2 A schematic flow chart of a method for obtaining a joint toxicity index between different pollutants according to the present invention; Figure 3 A schematic diagram of an evaluation system for the pollution reduction and carbon reduction effect of urban waste recycling and treatment according to the present invention; Figure 4 This is a schematic diagram of the interface of the evaluation system for the pollution reduction and carbon reduction effect of urban waste recycling and treatment according to the present invention. DETAILED DESCRIPTION

[0020] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0021] Example 1

[0022] See also Figure 1 As shown, the method for evaluating the pollution reduction and carbon reduction effect of urban waste recycling and treatment described in this embodiment includes the following steps: N sampling points are arranged at the urban domestic waste recycling and treatment points, and garbage samples in different states are collected according to the preset sampling frequency. The garbage samples in different states include solid garbage samples, liquid garbage samples and gaseous garbage samples; collecting garbage samples from different areas and at different times of the urban domestic waste recycling and treatment points can more accurately reflect the microbial status of domestic waste in different time and space states, and can comprehensively understand the pollution components and potential hazards of urban domestic waste, provide support for pollution reduction and carbon reduction evaluation, and help to accurately assess the pollution pathways and risks of garbage in different environmental media.

[0023] Multi-omics analysis was performed on garbage samples in different states to obtain microbial gene abundance, gene expression and protein abundance; microbial gene abundance reflects the types and numbers of microorganisms in a specific environment. In scenarios such as garbage disposal, a higher abundance of microbial genes related to the degradation of pollutants or participation in the carbon cycle means that the environment has a greater potential for pollution reduction and carbon reduction; for example, microbial communities with rich genes for degrading organic pollutants may more effectively decompose organic matter in garbage and reduce pollutant emissions; and microorganisms containing a large number of carbon fixation genes may play an important role in carbon fixation and help reduce carbon emissions. Gene expression can reflect the actual execution potential of microorganisms for related functions in a specific environment; for example, in a garbage disposal system, when environmental conditions are suitable, the expression of genes related to methane oxidation increases, indicating that microorganisms have a stronger ability to convert methane into carbon dioxide and water, thereby reducing the emission of methane, a potent greenhouse gas, which has positive significance for pollution reduction and carbon reduction. Protein is the ultimate executor of gene function, and protein abundance directly reflects the ability of microorganisms to actually participate in the process of pollution reduction and carbon reduction. A higher abundance of proteins related to pollutant degradation enzymes or carbon metabolism indicates that the microorganisms are actively carrying out related physiological activities, which can more intuitively reflect the actual role of microorganisms in pollution reduction and carbon reduction.

[0024] Methods for obtaining microbial gene abundance include: Obtain a known microbial genome database and extract microorganisms from garbage samples in different states; For microorganisms with DNA as genetic material, cell lysis and DNA purification are performed to obtain extracted DNA, and the extracted DNA is subjected to high-throughput sequencing, and the similarity between the DNA sequence data obtained by sequencing and a known microbial genome database is calculated, and the data is compared with a preset DNA similarity threshold. When the similarity is higher than the DNA similarity threshold, the corresponding microbial species in the microbial genome database is used as the type of the extracted microorganism; for microorganisms with RNA as genetic material, cell lysis, RNA separation and reverse transcription are performed to obtain extracted cDNA, and the extracted cDNA is subjected to high-throughput sequencing, and the similarity between the cDNA sequence data obtained by sequencing and a known microbial genome database is calculated, and the data is compared with a preset cDNA similarity threshold. When the similarity is higher than the cDNA similarity threshold, the corresponding microbial species in the microbial genome database is used as the type of the extracted microorganism; According to the type of microorganism, gene prediction is performed on the sequence data based on gene prediction software to obtain the position and sequence of each gene, and the number of reads of each gene in the sequence data is counted. The number of reads represents the number of corresponding genes read from DNA or RNA. The ratio of the number of reads of each gene in the sequence data to the total number of reads of all genes in the sequence data is calculated, and the ratio is used as the gene abundance.

[0025] Methods for obtaining microbial gene expression include: The microbial gene expression was calculated by comparing the number of reads of each gene in the sequence data and the total number of reads of all genes in the sequence data during the process of obtaining the microbial gene abundance. : ;in, is the number of gene reads, is the total number of reads for all genes, is the exon length of the gene, which is obtained by counting the lengths of all components corresponding to the gene.

[0026] Methods for obtaining microbial protein abundance include: The microorganisms are cultured in a preset culture medium, the microbial cells are ruptured by ultrasonic disruption, the proteins in the cells are extracted, a liquid chromatography system is formed by a liquid chromatography column and a mobile phase, the extracted proteins are injected into the liquid chromatography system, the mobile phase carries the proteins through the liquid chromatography column, the separated protein components flowing out of the liquid chromatography column enter the mass spectrometer, and then ionized to obtain protein ions, the protein ions are separated and detected in the mass analyzer of the mass spectrometer according to the mass-to-charge ratio of the protein ions, the mass spectrometry signal intensity and the total mass spectrometry signal intensity of the protein are obtained, and the ratio of the mass spectrometry signal intensity of the protein to the total mass spectrometry signal intensity is used as the protein abundance.

[0027] Determine the content of different pollutants in garbage samples in different states, as well as the activity data and emission factors in the process of urban domestic waste recycling and treatment; the content of different pollutants is determined by chemical methods, such as gas chromatography-mass spectrometry and atomic absorption spectroscopy; pollutants include conventional pollutants (such as organic, inorganic and nutrients), new pollutants (such as microplastics, ARGs, POPs and EDCs), gaseous pollutants (such as greenhouse gases and odorous gases) and other pollutants (such as pathogenic microorganisms and radioactive substances); collecting the content of different pollutants in garbage samples in different states can determine the specific types of various pollutants, which helps to fully understand the composition and degree of pollution of pollutants in garbage, and provide basic data for pollution reduction and carbon reduction.

[0028] Activity data include energy consumption data, material consumption data, transportation data and waste treatment data; energy consumption data include the usage of electricity and fuel (such as coal, natural gas, gasoline); material consumption data include the usage of raw materials and chemicals; transportation data include transportation distance and type of transportation tool (such as trucks, ships, airplanes); waste treatment data include carbon emission data of different waste treatment methods; emission factors include fuel carbon emission factors, electricity carbon emission factors and transportation tool carbon emission factors, which can be obtained through international standards, national or regional databases, and industry reports; collecting activity data can clarify all carbon emission data in the process of urban domestic waste recycling and treatment, which is convenient for the subsequent accurate calculation of full-cycle carbon emissions; collecting different emission factors can quantify emission levels and accurately calculate carbon emission data.

[0029] The joint toxicity index between different pollutants is analyzed based on the content of different pollutants, and the full-cycle carbon footprint is analyzed based on the activity data and emission factors in the recycling and treatment process of urban domestic waste; the full-cycle carbon footprint includes the carbon footprint of unit products and per capita carbon footprint in the whole cycle.

[0030] See also Figure 2 , methods for obtaining the joint toxicity index between different pollutants include: Step 1, pre-selecting experimental microorganisms, and conducting a single pollutant toxicity test on each pollutant according to the type of pollutant, obtaining the median lethal concentration of each pollutant for the pre-selected experimental microorganisms, performing equal toxicity ratios for any two different types of pollutants according to the median lethal concentrations, exposing the pre-selected experimental microorganisms to single pollutants of different concentrations, and recording the corresponding mortality rate; exposing the pre-selected experimental microorganisms to pollutant mixtures of different concentrations, recording the corresponding mortality rate, fitting the dose-response curve for the single pollutant or the pollutant mixture based on the probability unit method, and calculating the corresponding median lethal concentration; Methods for calculating the LC50 include: Convert mortality rate to probability units : ; in, is the inverse function of the standard normal distribution; for mortality; The logarithm of the pollutant concentration As the independent variable, The value is the dependent variable, and the linear regression fitting is performed to obtain the regression equation, where is the pollutant concentration: ;in, and is the fitting parameter; the logarithm of the pollutant concentration And the corresponding Substitute the values ​​into the regression equation for the fitting parameters and Solve the equation to obtain the corresponding regression equation, and use the corresponding regression equation as the dose-response curve equation; when When the dose-response curve equation is used, the pollutant concentration corresponding to the dose-response curve equation is calculated, and the corresponding pollutant concentration is taken as the corresponding half-lethal concentration.

[0031] Step 2: Calculate the toxicity unit of a single pollutant based on the median lethal concentration of the single pollutant : ; Step 3: Calculate the total toxicity unit of the mixture based on the toxicity unit of a single pollutant ; ; in, is the total number of pollutant types in the mixture; Step 4: Calculate the combined toxicity index : ;in, It indicates that there is a synergistic effect between different pollutants in the mixture; It means that there is an additive effect between different pollutants in the mixture. It indicates that there is antagonism between different pollutants in the mixture.

[0032] Methods for obtaining a full-cycle carbon footprint include: Calculate the carbon emissions of the entire cycle to obtain the total carbon emissions, and calculate the carbon footprint of each unit product and per capita in the entire cycle; Methods for obtaining unit product carbon footprint and per capita carbon footprint include: Calculation of direct emissions: ; Calculation of indirect emissions: ; Calculation of other indirect emissions: ; Calculate total carbon emissions: ; Calculate the carbon footprint per unit product: ; Calculate the carbon footprint per person: .

[0033] The obtained microbial gene abundance, microbial gene expression, microbial protein abundance, joint toxicity index and full-cycle carbon footprint were standardized; principal component analysis was then performed on the standardized microbial gene abundance, gene expression, protein abundance, joint toxicity index and full-cycle carbon footprint to obtain the corresponding principal component characteristics; Methods for obtaining principal component features include: The standardized variables are organized into a data matrix, where each row represents a garbage sample and each column represents a variable; the covariance matrix of the data matrix is ​​calculated based on the following formula: : ; in, is the number of garbage samples; After standardization dimensional data matrix, is the number of variables; is the transpose of a vector; Perform eigenvalue decomposition on the covariance matrix and obtain The eigenvalues ​​corresponding to the garbage samples and the corresponding eigenvector ; Among them, the eigenvalue represents the variance of the principal component. The larger the variance, the more information the corresponding principal component contains; the eigenvector represents the direction of the principal component; Methods for eigenvalue decomposition of the covariance matrix include: For the covariance matrix , calculate the eigenvalues ​​and corresponding eigenvectors so that the eigenvector equation Established, that is Established, among which, is the characteristic value; is the feature vector; for dimensional identity matrix; Constructing the characteristic equation Make the eigenvector equation have non-zero solutions, solve the characteristic equation to obtain the eigenvalue The value of The eigenvalues ​​corresponding to the garbage samples Substitute the eigenvector equation, obtain and solve the homogeneous linear equations corresponding to the eigenvector equation, and get the corresponding eigenvector ; Sort the eigenvalues ​​in descending order and select the top eigenvalues ​​based on the cumulative variance contribution rate. The eigenvectors corresponding to the largest eigenvalues ​​form a new matrix , cumulative variance contribution rate The calculation of is as follows: ;in, For the The eigenvalues ​​corresponding to the principal components; Based on the new matrix The standardized data matrix Project onto the selected principal component to obtain the reduced-dimensional data matrix ,in, For one dimensional matrix, that is, each garbage sample is The dimension feature is transformed into dimensional features; the reduced dimensionality data matrix as the principal component features.

[0034] The principal component characteristics are used as the input of the index analysis model to obtain the pollution reduction and carbon reduction index value, and the pollution reduction and carbon reduction evaluation is carried out based on the pollution reduction and carbon reduction index value and the principal component characteristics; The training methods of the indicator analysis model include: M groups of garbage sample data are collected in advance, and the garbage sample data include principal component characteristics and corresponding pollution reduction and carbon reduction index values; the principal component characteristics are used as the input of the index analysis model, and the pollution reduction and carbon reduction index values ​​are used as the output of the index analysis model, the index analysis model is trained, and the model parameters of the index analysis model are adjusted based on the gradient descent algorithm to obtain the index analysis model corresponding to the model parameters that minimize the error of the index analysis model as the trained index analysis model.

[0035] Methods for evaluating pollution reduction and carbon reduction based on pollution reduction and carbon reduction index values ​​and main component characteristics include: Calculate the Information entropy of principal components ;in, ; For the The first sample of garbage principal components; Calculate the The information entropy weight of the principal component ; Calculate the comprehensive evaluation index : ; in, For the pollution reduction and carbon reduction index values; For the The pollution reduction and carbon reduction index value is The influence coefficients of the principal components; The value can be used to evaluate the pollution reduction and carbon reduction effects of different garbage samples. The larger the value, the better the pollution reduction and carbon reduction effect; The values ​​are compared with the preset index ranges to divide the pollution reduction and carbon reduction levels, providing a basis for formulating comprehensive prevention and control measures.

[0036] Example 2 See also Figure 3 As shown, the evaluation system for the pollution reduction and carbon reduction effect of urban waste recycling and treatment described in this embodiment includes: The first collection module: arrange N sampling points at the urban domestic waste recycling and processing points, and collect garbage samples in different states according to the preset sampling frequency. The garbage samples in different states include solid garbage samples, liquid garbage samples and gaseous garbage samples; Multi-omics analysis module: Multi-omics analysis of garbage samples in different states to obtain microbial gene abundance, gene expression and protein abundance; The second collection module: Determine the content of different pollutants in garbage samples of different states, as well as the activity data and emission factors in the process of urban domestic waste recycling and treatment; Data analysis module: Analyze the joint toxicity index of different pollutants based on the content of different pollutants, and analyze the full-cycle carbon footprint based on the activity data and emission factors in the process of urban domestic waste recycling and treatment; Principal component extraction module: Standardize the variables corresponding to the garbage samples in different states, including microbial gene abundance, microbial gene expression, microbial protein abundance, joint toxicity index and full-cycle carbon footprint; then perform principal component analysis on the standardized variables to obtain the principal component characteristics; Comprehensive evaluation module: The principal component characteristics are used as the input of the index analysis model to obtain the pollution reduction and carbon reduction index values, and pollution reduction and carbon reduction evaluation is performed based on the pollution reduction and carbon reduction index values ​​and the principal component characteristics.

[0037] Reference Figure 4 As of now, the total number of sampling points has reached 142, the total number of samples is 3,721, the total carbon emissions are 256.3 tons, and the comprehensive score is 87.5 points. In terms of pollutant content trends, indicators such as chemical oxygen demand (COD), ammonia nitrogen, and total phosphorus fluctuate in different months. Carbon footprint analysis shows that transportation, landfill, incineration, composting and other links each have their own share in the carbon footprint. In the latest sampling data, the solid waste sample collected at the first sampling point had a pollutant content of 21.5 mg / L; the liquid waste sample collected at the second sampling point had a pollutant content of 18.2 mg / L, and the status was normal. From the overall data, the work of pollution reduction and carbon reduction has achieved certain results, with a high comprehensive score and pollutant content within a controllable range, but it is still necessary to continue to pay attention to the fluctuation of pollutant content and further optimize each link to improve the effectiveness of pollution reduction and carbon reduction.

[0038] The above is only a specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art can easily think of changes or substitutions within the technical scope disclosed by the present invention, which should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention shall be based on the protection scope of the claims.

[0039] Finally: The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for evaluating the pollution reduction and carbon reduction effects of urban waste recycling and treatment, characterized in that: The steps include: Arrange N sampling points at the urban domestic waste recycling and processing points to collect waste samples in different states according to the preset sampling frequency. The waste samples in different states include solid waste samples, liquid waste samples and gaseous waste samples; Multi-omics analysis was performed on garbage samples in different states to obtain microbial gene abundance, gene expression, and protein abundance; Determination of the content of different pollutants in waste samples of different states, as well as activity data and emission factors in the process of municipal solid waste recycling; Analyze the joint toxicity index between different pollutants based on the content of different pollutants, and analyze the full-cycle carbon footprint based on the activity data and emission factors in the urban domestic waste recycling process; The variables corresponding to the garbage samples of different states were standardized, including microbial gene abundance, microbial gene expression, microbial protein abundance, joint toxicity index and full-cycle carbon footprint; principal component analysis was then performed on the standardized variables to obtain the principal component characteristics; The principal component characteristics are used as the input of the index analysis model to obtain the pollution reduction and carbon reduction index values, and the pollution reduction and carbon reduction evaluation is carried out based on the pollution reduction and carbon reduction index values ​​and the principal component characteristics.

2. The method for evaluating the pollution reduction and carbon reduction effect of urban waste recycling and treatment according to claim 1, characterized in that: Methods for obtaining principal component features include: Arrange the standardized variables into a data matrix, where each row represents a garbage sample and each column represents a variable; calculate the covariance matrix of the data matrix; Perform eigenvalue decomposition on the covariance matrix and obtain The eigenvalues ​​corresponding to the garbage samples and the corresponding eigenvector ; Sort the eigenvalues ​​in descending order and select the top eigenvalues ​​based on the cumulative variance contribution rate. The eigenvectors corresponding to the largest eigenvalues ​​form a new matrix ; Based on the new matrix The standardized data matrix Project onto the selected principal component to obtain the reduced-dimensional data matrix ; The reduced data matrix as the principal component features.

3. The method for evaluating the pollution reduction and carbon reduction effect of urban waste recycling and treatment according to claim 2, characterized in that: Methods for eigenvalue decomposition of the covariance matrix include: For the covariance matrix , calculate the eigenvalue and the corresponding eigenvector, construct and make the eigenvector equation valid; Construct the characteristic equation so that the characteristic vector equation has a non-zero solution; The eigenvalues ​​corresponding to the garbage samples Substitute the eigenvector equation, obtain and solve the homogeneous linear equations corresponding to the eigenvector equation, and get the corresponding eigenvector .

4. The method for evaluating the pollution reduction and carbon reduction effect of urban waste recycling and treatment according to claim 1, characterized in that: The training methods of the indicator analysis model include: M groups of garbage sample data are collected in advance, and the garbage sample data include principal component characteristics and corresponding pollution reduction and carbon reduction index values; the principal component characteristics are used as the input of the index analysis model, and the pollution reduction and carbon reduction index values ​​are used as the output of the index analysis model, the index analysis model is trained, and the model parameters of the index analysis model are adjusted based on the gradient descent algorithm to obtain the index analysis model corresponding to the model parameters that minimize the error of the index analysis model as the trained index analysis model.

5. The method for evaluating the pollution reduction and carbon reduction effect of urban waste recycling and treatment according to claim 1, characterized in that: Methods for evaluating pollution reduction and carbon reduction based on pollution reduction and carbon reduction index values ​​and main component characteristics include: Calculate the The information entropy of the principal components and the corresponding information entropy weights; then calculate the comprehensive evaluation index .

6. The method for evaluating the pollution reduction and carbon reduction effect of urban waste recycling and treatment according to claim 1, characterized in that: Methods for obtaining joint toxicity indices among different pollutants include: Step 1, pre-selecting experimental microorganisms, and conducting a single pollutant toxicity test on each pollutant according to the type of pollutant, obtaining the median lethal concentration of each pollutant for the pre-selected experimental microorganisms, performing equal toxicity ratios for any two different types of pollutants according to the median lethal concentrations, exposing the pre-selected experimental microorganisms to single pollutants of different concentrations, and recording the corresponding mortality rate; exposing the pre-selected experimental microorganisms to pollutant mixtures of different concentrations, recording the corresponding mortality rate, fitting the dose-response curve for the single pollutant or the pollutant mixture based on the probability unit method, and calculating the corresponding median lethal concentration; Step 2: Calculate the toxicity unit of a single pollutant based on the median lethal concentration corresponding to the single pollutant; Step 3: Calculate the total toxicity unit of the mixture based on the toxicity unit of the single pollutant; Step 4: Calculate the combined toxicity index based on the corresponding median lethal concentration of the pollutant mixture and the total toxicity unit of the mixture.

7. The method for evaluating the pollution reduction and carbon reduction effect of urban waste recycling and treatment according to claim 6, characterized in that: Methods for calculating LC50 include: Convert mortality rate to probability units ; Logarithm of pollutant concentration As the independent variable, The value is the dependent variable, and the linear regression fitting is performed to obtain the regression equation, where is the pollutant concentration; the logarithm of the pollutant concentration And the corresponding Substitute the values ​​into the regression equation to solve the fitting parameters and obtain the corresponding regression equation, which is used as the dose-response curve equation; when When the dose-response curve equation is used, the pollutant concentration corresponding to the dose-response curve equation is calculated, and the corresponding pollutant concentration is taken as the corresponding half-lethal concentration.

8. The method for evaluating the pollution reduction and carbon reduction effect of urban waste recycling and treatment according to claim 1, characterized in that: Methods for obtaining a full-cycle carbon footprint include: Calculate the carbon emissions of the entire cycle to obtain the total carbon emissions, and calculate the carbon footprint of each unit product and per capita in the entire cycle; Methods for obtaining unit product carbon footprint and per capita carbon footprint include: Calculate direct emissions, indirect emissions and other indirect emissions separately; calculate total carbon emissions based on the direct emissions, indirect emissions and other indirect emissions; calculate the carbon footprint per unit product and per capita carbon footprint separately based on the total carbon emissions.

9. The method for evaluating the pollution reduction and carbon reduction effect of urban waste recycling and treatment according to claim 1, characterized in that: Methods for obtaining microbial gene abundance include: Obtain a known microbial genome database and extract microorganisms from garbage samples in different states; For microorganisms with DNA as genetic material, cell lysis and DNA purification are performed to obtain extracted DNA, and the extracted DNA is subjected to high-throughput sequencing, and the similarity between the DNA sequence data obtained by sequencing and a known microbial genome database is calculated, and the data is compared with a preset DNA similarity threshold. When the similarity is higher than the DNA similarity threshold, the corresponding microbial species in the microbial genome database is used as the type of the extracted microorganism; for microorganisms with RNA as genetic material, cell lysis, RNA separation and reverse transcription are performed to obtain extracted cDNA, and the extracted cDNA is subjected to high-throughput sequencing, and the similarity between the cDNA sequence data obtained by sequencing and a known microbial genome database is calculated, and the data is compared with a preset cDNA similarity threshold. When the similarity is higher than the cDNA similarity threshold, the corresponding microbial species in the microbial genome database is used as the type of the extracted microorganism; According to the type of microorganism, gene prediction is performed on the sequence data based on gene prediction software to obtain the position and sequence of each gene, and the number of reads of each gene in the sequence data is counted. The number of reads represents the number of corresponding genes read from DNA or RNA. The ratio of the number of reads of each gene in the sequence data to the total number of reads of all genes in the sequence data is calculated, and the ratio is used as the gene abundance.

10. The method for evaluating the pollution reduction and carbon reduction effect of urban waste recycling and treatment according to claim 9, characterized in that: Methods for obtaining microbial gene expression include: The microbial gene expression was calculated by comparing the number of reads of each gene in the sequence data and the total number of reads of all genes in the sequence data in the process of obtaining the microbial gene abundance.

11. The method for evaluating the pollution reduction and carbon reduction effect of urban waste recycling and treatment according to claim 1, characterized in that: Methods for obtaining microbial protein abundance include: The microorganisms are cultured in a preset culture medium, the microbial cells are ruptured by ultrasonic disruption, the proteins in the cells are extracted, a liquid chromatography system is formed by a liquid chromatography column and a mobile phase, the extracted proteins are injected into the liquid chromatography system, the mobile phase carries the proteins through the liquid chromatography column, the separated protein components flowing out of the liquid chromatography column enter the mass spectrometer, and then ionized to obtain protein ions, the protein ions are separated and detected in the mass analyzer of the mass spectrometer according to the mass-to-charge ratio of the protein ions, the mass spectrometry signal intensity and the total mass spectrometry signal intensity of the protein are obtained, and the ratio of the mass spectrometry signal intensity of the protein to the total mass spectrometry signal intensity is used as the protein abundance.

12. An evaluation system for the pollution reduction and carbon reduction effect of urban waste recycling and treatment, used to implement the evaluation method for the pollution reduction and carbon reduction effect of urban waste recycling and treatment as claimed in any one of claims 1 to 11, characterized in that: include: The first collection module: arrange N sampling points at the urban domestic waste recycling and processing points, and collect garbage samples in different states according to the preset sampling frequency. The garbage samples in different states include solid garbage samples, liquid garbage samples and gaseous garbage samples; Multi-omics analysis module: Multi-omics analysis of garbage samples in different states to obtain microbial gene abundance, gene expression and protein abundance; The second collection module: Determine the content of different pollutants in garbage samples of different states, as well as the activity data and emission factors in the process of urban domestic waste recycling and treatment; Data analysis module: Analyze the joint toxicity index of different pollutants based on the content of different pollutants, and analyze the full-cycle carbon footprint based on the activity data and emission factors in the process of urban domestic waste recycling and treatment; Principal component extraction module: Standardize the variables corresponding to the garbage samples in different states, including microbial gene abundance, microbial gene expression, microbial protein abundance, joint toxicity index and full-cycle carbon footprint; then perform principal component analysis on the standardized variables to obtain the principal component characteristics; Comprehensive evaluation module: The principal component characteristics are used as the input of the index analysis model to obtain the pollution reduction and carbon reduction index values, and pollution reduction and carbon reduction evaluation is performed based on the pollution reduction and carbon reduction index values ​​and the principal component characteristics.

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