CN116307913A - Comprehensive multi-level sewage treatment facility pollutant reduction efficiency evaluation method and system - Google Patents
Comprehensive multi-level sewage treatment facility pollutant reduction efficiency evaluation method and system Download PDFInfo
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Abstract
The invention relates to the technical field of pollutant reduction efficiency evaluation, and provides a comprehensive multi-level sewage treatment facility pollutant reduction efficiency evaluation method and system. The method utilizes FHW method to evaluate the reliability of each level index, preselects key evaluation indexes for reducing efficiency, then organically combines the analytic hierarchy process with the fuzzy analysis method, constructs a judgment matrix by the analytic hierarchy process, determines the weight of the key indexes, determines the membership of the evaluation level by the fuzzy analysis method, carries out multistage fuzzy comprehensive evaluation, realizes the unification of qualitative evaluation and quantitative evaluation, and further establishes a sewage treatment facility pollutant reduction efficiency evaluation system. According to the invention, the preselection of the efficiency evaluation index is realized through a FHW method, the defects of the traditional analytic hierarchy process are overcome, the objectivity and the reliability of the analytic hierarchy process are improved, the evaluation grade of the reduction efficiency of the treatment facility is determined through membership calculation, and an evaluation system support is provided for the cooperative reduction efficiency evaluation of the conventional pollutants and the new pollutants of the sewage treatment facility.
Description
Technical Field
The invention belongs to the technical field of pollutant reduction efficiency evaluation, and particularly relates to a comprehensive multi-level sewage treatment facility pollutant reduction efficiency evaluation method and system.
Background
At present, sewage treatment facilities have emerged different treatment technologies for removing various pollutants such as conventional pollutants, characteristic new pollutants and the like. Different treatment techniques have advantages and disadvantages, and the pollutant reduction performance achieved by the treatment techniques also varies. Therefore, there is a need to develop a comprehensive and accurate evaluation method for pollutant reduction efficiency of sewage treatment facilities, and establish a complete evaluation system, so as to comprehensively evaluate the synergistic reduction efficiency of different treatment technology units on various indexes such as conventional pollutants and characteristic new pollutants from different angles, thereby identifying a high-efficiency low-carbon type pollutant synergistic removal technology with high removal efficiency and low economic cost, and having practical significance on upgrading and modifying the existing urban sewage treatment plant and effectively removing the characteristic new pollutants.
The characteristic new pollutants are pollutants generated in production construction or other activities, which are harmful to life and ecological environment and are caused by human activities and are clearly existing at present but are not regulated or incompletely regulated by legal regulations and standards. The new contaminant characteristics that have been found worldwide are now over 20 broad classes, each containing tens or even hundreds of compounds. Scientific demonstration proves that some typical characteristic new pollutants can cause great harm to human body and ecological system health. Various methods have been reported for the abatement and removal of characteristic new contaminants, such as biological, adsorption, chemical oxidation, membrane technology, advanced oxidation, and the like. These techniques have respective advantages and disadvantages. For example, biological methods are easier to implement for large-scale applications, but their removal efficiency is low and unstable; the ozone oxidation method and the membrane technology can realize higher removal rate, but have the problems of high operation cost, high energy consumption and the like.
The pollutant reduction process is influenced by multiple factors, the number of evaluation indexes is large, the related range is wide, the index importance is difficult to quantify, and the conventional index preselection method has no application in the aspect of pollutant reduction efficiency evaluation. As the degradation and reduction process of pollutants in sewage treatment facilities is a complex process, the selection of evaluation index standards is fuzzy, and a reasonable comprehensive evaluation method is difficult to form to finally determine the evaluation grade. In addition, the research and application fields of the existing efficiency evaluation methods are not yet involved in evaluation of the cooperative removal efficiency of conventional pollutants and characteristic new pollutants in sewage treatment facilities, and some efficiency evaluation methods are not suitable for evaluating the removal efficiency of the characteristic new pollutants and the energy-saving and carbon-reduction level of the sewage treatment facilities.
Disclosure of Invention
The invention provides a comprehensive multi-level sewage treatment facility pollutant reduction efficiency evaluation method and system, so as to form a pollutant reduction efficiency evaluation system based on an analytic hierarchy process-fuzzy analytic process, and fill the technical blank in the field of sewage treatment facility pollutant cooperative reduction efficiency evaluation.
The invention relates to a sewage treatment facility pollutant reduction efficiency evaluation method, which comprises the following steps:
S1: setting conventional pollutants and characteristic new pollutant reduction efficiency related indexes of a sewage treatment facility, wherein the conventional pollutants and characteristic new pollutants comprise candidate primary evaluation indexes and candidate secondary evaluation indexes; each candidate first-level evaluation index corresponds to a plurality of candidate second-level evaluation indexes; the candidate first-level evaluation indexes comprise resource consumption, pollutant generation, environmental benefit, economic cost, technical performance and management class;
s2: evaluating the candidate first-level evaluation index and the candidate second-level evaluation index by a FHW method to obtain an evaluation result; setting screening standards, and determining a first-level evaluation index and a second-level evaluation index according to the evaluation result and the screening standards;
s3: determining the weight value of the first-level evaluation index and the second-level evaluation index;
s4: constructing an index system grading standard to form a plurality of grades; acquiring original data of a sewage treatment facility to be evaluated; performing multi-level fuzzy comprehensive evaluation according to the original data and the index system grading standard to obtain membership values of evaluation indexes of each level in each level;
s5: and comprehensively evaluating according to the weight values and membership values of the first-level evaluation index and the second-level evaluation index to obtain a pollutant reduction efficiency evaluation result of the sewage treatment facility to be evaluated.
Optionally, the candidate secondary evaluation indexes corresponding to the resource consumption comprise raw material consumption of unit product, fresh water consumption of unit product and electricity consumption of unit product; the candidate secondary evaluation indexes corresponding to the pollutant generation comprise the unit product wastewater generation amount, the unit product pollutant generation amount and the overall water balance condition of the treatment facility; the candidate secondary evaluation indexes corresponding to the environmental benefits comprise characteristic new pollutant removal rates and conventional pollutant removal rates; the candidate secondary evaluation indexes corresponding to the economic cost comprise ton water investment cost and ton water pollutant treatment cost; the candidate secondary evaluation indexes corresponding to the technical performance comprise the technical maturity, the removal pertinence of conventional pollutants and the removal pertinence of characteristic new pollutants; and the candidate secondary evaluation indexes corresponding to the management class comprise an automation level and a treatment facility energy-saving and carbon-reducing level.
Optionally, in step S2, evaluating the candidate primary evaluation index and the candidate secondary evaluation index by a FHW method includes:
s21: constructing a FHW expert consultation table, and grading the candidate primary evaluation index and the candidate secondary evaluation index for two rounds by a plurality of experts according to the FHW expert consultation table; averaging two groups of data obtained in the two rounds of scoring to form an evaluation matrix U;
U in the formula 1 ，u 2 ，...，u k Evaluating for a subject; (p) 1 ，a 1 )，(p 2 ，a 2 )，...，(p k ，a k ) Is a gray figure of merit, where p k Is the obvious goodness of the kth index, a k Potential goodness for the kth indicator; (q) 1 ，b 1 )，(q 2 ，b 2 )，…，(q k ，b k ) Is gray in degree, where q k B is the obvious degree of deterioration of the kth index k Potential inferior degree of the kth index;
s22: determining decision weight values fi of the plurality of experts;
s23: according to the evaluation matrix U and the decision weight fi of each expert, calculating to obtain each index item Y k Principal score value T k White superior-inferior ratio C k Gray superior-inferior ratio D k The method comprises the steps of carrying out a first treatment on the surface of the Wherein:
T k ＝Σu ki fi
wherein: u (u) ki As index item Y k I-th expert two-round scoring u for subject evaluation of (2) k Average value of (2); the index item Y k The method comprises the steps of respectively candidate first-level evaluation indexes and candidate second-level evaluation indexes;
wherein: p is p k ＝Σp ki f i ，q k ＝∑q ki f i ，p ki Q ki Respectively index item Y k Apparent goodness p k And a degree of conspicuity q k An average of two rounds of scoring by the ith expert;
wherein: a, a k ＝∑a ki f i ，b k ＝∑b ki f i ，a ki B ki Respectively isIndex item Y k Potential goodness a k And potential inferior degree b k The average of the scores of the ith expert in the two rounds.
Optionally, the evaluation result in step S2 includes: the main grading values of the candidate first-grade evaluation indexes and the candidate second-grade evaluation indexes, the white superior-inferior ratio and the gray superior-inferior ratio; the screening criteria are: the main grading value is more than 80 points, and the white superior-inferior ratio and the gray superior-inferior ratio are both more than 1.
Optionally, step S22 includes:
s221: determining all decision weight evaluation indexes as academic achievements in the aspects of relevant research, pollutant reduction evaluation, familiarity degree of the performance evaluation and caution attitude of the evaluation;
s222: assigning scores to each decision weight evaluation index of each expert, and then calculating to obtain a decision weight fi of each expert according to the weight value of each decision weight evaluation index and the following formula;
fi＝λ 1 Ei+λ 2 Zi+λ 3 Ci+λ 4 the Li is characterized in that Ei, zi, ci, li sequentially and respectively represents the scoring values of four decision weight evaluation indexes, namely academic achievements of an ith expert in relevant research over 3 years, pollutant reduction evaluation, familiarity degree of the performance evaluation and caution attitude of the evaluation; lambda (lambda) 1 -λ 4 The weight values of the decision weight evaluation indexes are 0.20,0.15,0.35,0.30 in sequence.
Optionally, step S3 includes:
s31: comparing and assigning the first-level evaluation index and the second-level evaluation index pairwise according to a 9-scale judging method;
s32: constructing a judgment matrix, and performing consistency inspection and normalization;
s33: and calculating to obtain the weight values of the first-level evaluation index and the second-level evaluation index.
Optionally, the several levels in step S4 include four levels of high performance, medium performance, and low performance; in the step S4, performing multi-level fuzzy comprehensive evaluation, and obtaining membership values of each evaluation index in each level includes: dividing each secondary evaluation index into a qualitative index and a quantitative index, wherein the qualitative index obtains a membership value through an expert scoring method, and the quantitative index obtains the membership value through membership function calculation; and quantitatively processing quantitative indexes in the secondary evaluation indexes corresponding to the primary evaluation indexes including resource consumption, pollutant generation, environmental benefit and economic cost by using a membership function calculation method.
Optionally, the first-level evaluation index further comprises a technical performance, and the second-level evaluation index corresponding to the technical performance is a qualitative index, including technical maturity, pertinence to removal of conventional pollutants and pertinence to removal of characteristic new pollutants.
Optionally, the end point values of the dividing sections of the four grades are a, b and c in sequence from small to large, and the formed sections are < a, a-b, b-c and > c;
the membership functions are constructed according to index system grading standards, and comprise larger membership functions and smaller membership functions;
For the larger membership function, when the original value X of the evaluation index is in the range of b-C, C of the larger membership function 1 B, C 2 C is; c when the original value X of the evaluation index is within the range of a-b 1 Is a, C 2 B is; the membership function f B1 (X) is as follows:
for the smaller membership function, when the original value X of the evaluation index is in the range of b-C, C of the smaller membership function 1 Is C, C 2 B is; c when the original value X of the evaluation index is within the range of a-b 1 B, C 2 A is a; the membership function f B2 (X) is as follows:
in another aspect of the present invention, there is provided a pollutant abatement performance evaluation system for a sewage treatment facility, comprising:
the evaluation index candidate module is used for screening and obtaining a first-level evaluation index and a second-level evaluation index from the candidate first-level evaluation index and the candidate second-level evaluation index through a FHW method;
the evaluation index weight determining module is used for determining weight values of the primary evaluation index and the secondary evaluation index;
the sewage treatment facility original data acquisition module is used for acquiring original data of the sewage treatment facility to be evaluated;
the multi-stage fuzzy comprehensive evaluation module is used for quantifying the original data through multi-stage fuzzy comprehensive evaluation to obtain membership values of evaluation indexes of each stage in each stage;
And the pollutant reduction efficiency evaluation module is used for obtaining the pollutant reduction efficiency evaluation result of the sewage treatment facility to be evaluated after comprehensive evaluation.
The reliability of each level index is evaluated by using a FHW method, and the reduction efficiency key evaluation index is preselected. And then organically combining an analytic hierarchy process with a fuzzy analysis process, constructing a judgment matrix by the analytic hierarchy process, determining key index weights, determining the membership of the evaluation level by the fuzzy analysis process, performing multi-level fuzzy comprehensive evaluation, realizing the unification of qualitative evaluation and quantitative evaluation, and further establishing a pollutant reduction efficiency evaluation system of the sewage treatment facility.
The beneficial effects of the invention are as follows:
(1) For the establishment of a treatment facility reduction efficiency evaluation index system, the evaluation index is preselected by a FHW method, and the established index system covers indexes of characteristic new pollutant removal efficiency, conventional pollutant removal efficiency, comprehensive pollutant removal energy consumption, unit product wastewater production, overall water balance of the treatment facility, reduction performance of the treatment facility, technical maturity and the like; the evaluation method preselects a plurality of key reduction evaluation indexes, can evaluate the cooperative reduction effect of the conventional pollutants and the characteristic new pollutants in the sewage treatment facility, and evaluates the energy consumption, the carbon resource utilization condition, the water balance condition and the like of the sewage treatment facility, and meets the current double-carbon background requirement.
(2) The method organically combines the analytic hierarchy process and the fuzzy analytic process, realizes the unification of qualitative evaluation and quantitative evaluation, constructs a complete comprehensive evaluation system, and preselects evaluation indexes by using a FHW method, thereby optimizing the analytic hierarchy process and improving the objectivity and reliability of the analytic hierarchy process and the fuzzy comprehensive evaluation method.
(3) The method evaluation system integrates a plurality of evaluation methods: FHW method evaluation index preselection-analytic hierarchy process-fuzzy analysis method, a complete reduction efficiency evaluation system is constructed, the defects of strong subjectivity, narrow coverage and low reliability of a common single evaluation method are overcome, the objectivity deficiency of the single evaluation method is improved through multiple rounds of expert evaluation, the system of the method is perfect, the evaluation system is accurate, and the feasibility is good.
(4) The method has the advantages that the pollutant reduction of the sewage treatment facility is a complex process, the selection of evaluation index standards is fuzzy, the evaluation system adopts a membership method in fuzzy mathematics in the evaluation process, the quantification method of each evaluation index is defined, the characteristic new pollutant reduction efficiency evaluation grade of the sewage treatment facility is determined, and compared with other comprehensive evaluation methods, the method is more suitable for reduction efficiency evaluation, and has strong applicability, reliability and effectiveness.
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FIG. 1 is a flow chart of the method of the present invention.
Detailed Description
Preferred embodiments of the present invention will be described in detail below with reference to the accompanying drawings and detailed description.
Taking a sewage treatment facility in a typical area as an example, a pollutant reduction efficiency evaluation system of the sewage treatment facility based on a analytic hierarchy process-fuzzy analytic process is established, and conventional pollutants and characteristic new pollutant reduction efficiency related indexes in the sewage treatment facility are evaluated, wherein a flow chart of the pollutant reduction efficiency evaluation method is shown in fig. 1. The specific implementation steps adopted are as follows:
(1) Curtailment performance evaluation index preselection
Setting conventional pollutants and characteristic new pollutant reduction efficiency related indexes of a sewage treatment facility, wherein the conventional pollutants and characteristic new pollutants comprise candidate primary evaluation indexes and candidate secondary evaluation indexes; the candidate first-level evaluation indexes comprise resource consumption, pollutant generation, environmental benefit, economic cost, technical performance, management class and the like, and each candidate first-level evaluation index corresponds to a plurality of candidate second-level evaluation indexes; for example, candidate secondary indicators corresponding to environmental benefit indicators include characteristic new contaminant removal rates, regular contaminant removal rates, waste water biotoxicity reduction rates, and the like. The candidate primary evaluation index and the candidate secondary evaluation index set in this embodiment are specifically shown in table 2 below.
As can be seen in table 2, candidate primary evaluation indexes include: resource consumption, pollutant generation, environmental benefit, economic cost, technical performance, management class, structure planning and aesthetic class, and staff environmental awareness and work enthusiasm; the candidate secondary indexes corresponding to the resource consumption are unit product raw material consumption, unit product fresh water consumption and unit product electricity consumption; the corresponding candidate secondary indexes of pollutant generation are the unit product wastewater generation amount, the unit product pollutant generation amount and the overall water balance condition of the treatment facility; the candidate secondary indexes corresponding to the environmental benefit are characterized by new pollutant removal rate, conventional pollutant removal rate, waste water biotoxicity reduction rate and ecological risk of tail water convection basin; the candidate secondary index corresponding to the economic cost is the ton water investment cost and ton water pollutant treatment cost; the candidate secondary indexes corresponding to the technical performance are the technical maturity, the removal pertinence of conventional pollutants, the removal pertinence of characteristic new pollutants, the reduction pertinence of biological toxicity of wastewater and the advanced degree of treatment technology; the candidate secondary evaluation indexes corresponding to the management class are automation level, energy saving and carbon reduction level of the processing facilities and performance assessment of facility maintenance personnel; the candidate secondary indexes corresponding to the structure planning and the aesthetic class are the rationality of the arrangement planning of the processing facilities, the greening coverage rate of the factory area and the design aesthetic property of the structure of the factory area; the candidate secondary indexes corresponding to the environmental awareness and the work enthusiasm of the staff are staff environmental protection technology qualification and certificate, staff attendance rate and staff basic environmental protection knowledge assessment.
Evaluating the candidate first-level evaluation index and the candidate second-level evaluation index by a FHW method to obtain an evaluation result; setting screening standards, and determining a first-level evaluation index and a second-level evaluation index according to the evaluation result and the screening standards.
FHW is a fuzzy gray primitive space method, which is an improvement and development of the Delphi method. The advantages of the Delphi method, the BS method (brain storm method) and the KT method are combined, and novel discipline ideas such as fuzzy mathematics, grey system theory, physical element analysis and the like are adopted, so that the associative thinking can be quantitatively processed. The Delphi consultation table is changed into a FHW consultation table, qualitative factors can be quantified, and a series of indexes can be calculated to comprehensively reflect the current and future merits of each evaluation item. Before evaluating the pollutant reduction efficiency in the treatment facility, the key reduction efficiency evaluation index with evaluation significance is required to be preselected so as to increase the objectivity and reliability of the subsequent comprehensive evaluation, and the FHW method has more advantages than the traditional expert consultation method and can better preselect the efficiency evaluation index.
Taking an evaluation index system of a toxic and harmful pollutant treatment technology in a typical industrial industry as a reference, and collecting related technology and equipment operation data of a sewage treatment facility in a certain typical area; preselecting evaluation indexes of the reduction efficiency of the sewage treatment facility by adopting a FHW method, and performing expert scoring on each index of the project according to a fuzzy gray matter element principle to form an evaluation matrix U as follows;
U in the formula 1 ，u 2 ，...，u k Evaluating for a subject; (p) 1 ，a 1 )，(p 2 ，a 2 )，...，(p k ，a k ) Is a gray figure of merit, where p k Is the obvious goodness of the kth index, a k Potential advantage for the kth indexA degree; (q) 1 ，b 1 )，(q 2 ，b 2 )，…，(q k ，b k ) Is gray in degree, where q k B is the obvious degree of deterioration of the kth index k Potential inferior degree of the kth index; (T, (P, a), (Q, B)) = (u 1 ，u 2 ，…，u k ，((p 1 ，a 1 )，(p 2 ，a 2 )，...，(p k ，a k ))，((q 1 ，b 1 )，(q 2 ，b 2 )，…，(q k ，b k ) A) is called an extended primitive, and all index values u, p, a, q and b are rated according to a percentage.
Construction of the evaluation matrix U: and constructing a FHW expert consultation table, and scoring the evaluated indexes by a plurality of experts according to the FHW expert consultation table, and performing two rounds of total evaluation scoring to determine the relevant values of the evaluation indexes of each level. Specifically, each expert fills in two rounds of evaluation tables, wherein the first round of evaluation tables are independently considered, a discussion is not held, and the A table is filled in; the second round of discussion is called up, association is stimulated, the discussion sequence is opposite to the filling sequence of the A form so as to prevent the inertia thinking, and the B form is filled. After evaluation, two sets of data are obtained to form a closed interval, namely (U, U '), and then an average value of the two sets of data is taken as a final score value U= (u+u')/2, so that an evaluation matrix U is formed.
Then determining the decision weight value of the invited expert, wherein the invited expert has to be provided with quality: the related study was conducted for more than 3 years (E), academic results in terms of pollutant abatement assessment (Z), familiarity with this performance assessment (C), and careful attitude of assessment (L). In order to embody different professional qualities of different experts in risk evaluation and more objectively evaluate the different professional qualities of the experts, the comprehensive qualities of the experts are represented by the 4 indexes, different consultation tables are respectively designed to determine the score value of each index of each expert, a review expert weight index table (the weights ki of the 4 indexes are respectively 0.20,0.15,0.35,0.30) is designed, and the decision weight fi of each expert is calculated by using the following formula.
fi＝λ 1 Ei+λ 2 Zi+λ 3 Ci+λ 4 Li
Wherein Ei represents the value of the ith expert in the decision weight evaluation index E, zi represents the value of the ith expert in the decision weight evaluation index Z, ci represents the value of the ith expert in the weight evaluation index C, and Li represents the value of the ith expert in the decision weight evaluation index L. Wherein the fi value is not more than 1 at maximum, and the addition is performed by calculating 1 when the fi value exceeds 1. Thus, an expert weight index set is obtained: f= (F1, F2, …, fi), and Σfi=1, i is the number of experts participating in the evaluation.
Table 1 shows values of index items of the FHW consulting table constructed in the present embodiment, decision weight values of three experts, and resource consumption of the evaluation matrix U.
Table 1 FHW expert consulting table and evaluation matrix portion example
According to the evaluation matrix U and the decision weight fi of each expert, calculating to obtain each index item Y k Principal score value T k White superior-inferior ratio C k Gray superior-inferior ratio D k The method comprises the steps of carrying out a first treatment on the surface of the Wherein:
T k ＝Σu ki fi
wherein: u (u) ki As index item Y k I-th expert two-round scoring u for subject evaluation of (2) k Average value of (2); the index item Y k The method comprises the steps of respectively candidate first-level evaluation indexes and candidate second-level evaluation indexes;
wherein: p is p k ＝Σp ki f i ，q k ＝Σq ki f i ，p ki Q ki Respectively index item Y k Apparent goodness p k And a degree of conspicuity q k An average of two rounds of scoring by the ith expert; c (C) k The value represents a significant benefit and disadvantage of the outcomeThe ratio must be greater than 1 (C k >1) It is practically useful, otherwise it is not considered.
Wherein: a, a k ＝Σa ki f i ，b k ＝Σb ki f i ，a ki B ki Respectively index item Y k Potential goodness a k And potential inferior degree b k An average of two rounds of scoring by the ith expert; d (D) k The value representing the ratio of the potential benefit to the potential disadvantage of a result must be greater than 1 (D k >1) It is practically useful, otherwise it is not considered.
As shown in table 1, taking the primary evaluation index "resource consumption" as an example, three experts are listed for scoring thereof, first, the subject evaluation score T k =86×0.3+82×0.3+83×0.4=83.6; white superior-inferior ratio C k ＝p k /q k = (60×0.3+70×0.3+65×0.4)/(10×0.3+30×0.3+10×0.4) = 4.0625; gray superior inferior ratio D k ＝a k /b k ＝(50×0.3+76×0.3+60×0.4)/(15×0.3+20×0.3+10×0.4)＝4.2621。
The result shows that the total score of the first-level evaluation index 'resource consumption' is 83.6, the grade is better, the ratio of the white to the gray is greater than 1, and the first-level evaluation index is feasible and can be selected.
By analogy, as shown in table 2, after 8 candidate primary evaluation indexes are pre-selected by FHW method, 6 level indexes with total evaluation score greater than 80 and white and gray superior-inferior ratio greater than 1 are selected as pre-selected primary evaluation indexes, which are respectively: resource consumption, pollutant generation, environmental benefits, economic costs, technical performance, and management classes. Similarly, index factors such as raw material consumption of unit products, wastewater production amount of unit products, removal rate (%) of characteristic new pollutants A, removal rate (%) of conventional pollutants B, treatment cost of ton water pollutants, pertinence of conventional pollutants removal, pertinence of characteristic new pollutants removal and the like are preselected as secondary evaluation indexes.
TABLE 2 evaluation index of contaminant reduction efficacy candidate levels for wastewater treatment facilities
(2) Constructing a judgment matrix and determining the weight value of the evaluation index
To further compare the importance between the primary and secondary key evaluation index factors preselected by the FHW method, the importance was further evaluated by the analytic hierarchy process using a 9-scale judgment method, with reference numerals 1 to 9 and their inverse being scaled, as shown in Table 3 below.
Table 3 matrix element assignment criteria table
And then inviting a plurality of related experts to judge the importance of the index of the previous level in pairs according to the index of the same level, assigning values to the relative importance of index factors through expert consultation, and constructing two-to-two judgment matrixes of different levels, wherein the two-to-two judgment matrixes are respectively listed as a primary index judgment matrix and a pollutant generation class-two index judgment matrix as shown in tables 4, 5, 6 and 7.
TABLE 4 first level index determination matrix
TABLE 5 first level index determination matrix
TABLE 6 pollutant generation secondary index determination matrix (expert 1)
TABLE 7 pollutant generation secondary index determination matrix (expert 2)
According to the judgment matrix, calculating the maximum eigenvalue and the corresponding eigenvector of the judgment matrix by using geometric mean (root), obtaining the weight value of each element of each layer, and carrying out consistency test, wherein the steps are as follows:
(1) Calculating the product Mi of each row of elements of the judgment matrix
(2) Calculating the nth root of Mi
(3) Vector pair
Normalization is carried out
Then w= (W 1 ，W 2 ，...，W n ) T I.e. the feature vector, i.e. the weight, that is calculated.
(4) Calculating the maximum characteristic root lambda of the judgment matrix max
Wherein A is an A-B judgment matrix, and n is the order of the judgment matrix.
For example, the product of each row of the first-order judgment matrix in table 4 is calculated to obtain Mi= [0.003968254,0.333333333,3,0.018518519, 36, 378] T The method comprises the steps of carrying out a first treatment on the surface of the Then calculate 6 times root available for each row product:
and then normalizing the obtained product to obtain the following steps: w (W) 1 ＝[0.05，0.11，0.16，0.07，0.24，0.37] T Wi is the feature vector evaluated by expert 1 of the ith primary index, namely the weight. Expert 2 evaluation of the same principle available, W 2 ＝[0.047，0.10，0.13，0.09，0.26，0.373] T The final first-order index weight is the average value of all expert evaluation weights, and W= [0.049,0.105,0.145,0.08,0.25,0.371 ]] T . Expert evaluation weight average value of pollutant generation secondary index is calculated in a similar way, and W' = [0.24,0.38,0.38 ]] T The index weight values of all the secondary evaluation indexes obtained by the similar calculation are shown in table 8.
Table 8 various index weights for pollutant reduction efficiency of sewage treatment facilities
Then calculate the maximum characteristic root lambda of the judgment matrix max First, first level index expert 1 evaluates
AW 1 ＝[0.05×1+0.11×1/2+0.16×1/3+0.07×1+0.24×1/6+0.37×1/7,
0.05×2+0.11×1+0.16×1/2+0.07×3+0.24×1/3+0.37×1/3,
0.05×1+0.11×1/3+0.16×1/3+0.07×1+0.24×1/3+0.37×1/2,
0.05×6+0.11×3+0.16×2+0.07×3+0.24×1+0.37×1/3,
0.05×7+0.11×3+0.16×3+0.07×2+0.24×3+0.37×1] T ＝[0.321,1.258,1.97,0.273,2.55,2.59] T ；
And then calculating:
λ ma1 ＝[0.321/0.05+0.703/0.11+0.98/0.16+0.475/0.07+1.52/0.24+2.39/0.37] T /6＝6.41；
similarly, the first level index expert 2 evaluates AW 2 ＝[0.289,0.654,0.88,0.553,1.65,2.359] T ；
λ max2 =6.38, so the first-order index expert evaluates λ max ＝(λ max1 +λ max2 )/2＝6.395。
In the same way, the pollutant generates a secondary index lambda max ′＝3.287。
To ensure reasonable results by analytic hierarchy process, the matrix a is determined by normalization processing to be aω=λ max And (3) carrying out consistency judgment on the weight value of the relative importance of the corresponding index factor relative to a certain element of the upper layer by adopting the following formula in the solution omega of omega:
when the matrix determines that there is complete consistency, ci=0, i.e., ci=0, λ max ＝λ 1 =n, the matrix has complete consistency.
The matrix average random consistency judgment index is as follows:
when CR is less than 0.10, the matrix can be judged to have satisfactory random consistency, in some special cases, the CR judgment value can be relaxed to 0.20, and if the consistency requirement is not met, the judgment matrix is required to be adjusted so as to meet the consistency requirement.
And after importance judgment is carried out on the evaluation layers, consistency check sum is carried out on the evaluation layers, total ordering is carried out on the layers, and weights of all indexes are calculated after consistency check is carried out. The results of the index consistency test are summarized in Table 9.
TABLE 9 index weight and consistency check
(3) Multistage fuzzy comprehensive evaluation
The degradation and reduction process of pollutants in sewage treatment facilities is a complex process, and the selection of evaluation index standards is fuzzy, so that the evaluation process can select a membership degree method in fuzzy mathematics, and finally, the risk level is determined. The fuzzy mathematical method is reasonable compared with other comprehensive evaluation methods.
Firstly, constructing an index system grading standard to form a plurality of grades; acquiring original data of a sewage treatment facility to be evaluated; and carrying out multi-level fuzzy comprehensive evaluation according to the original data and the index system grading standard to obtain membership values of evaluation indexes of each level in each level. The index system classification standard is an important basis for determining the membership degree of each classification of enterprises. The index system grading standard is obtained by repeatedly comparing and correcting on the basis of field investigation of sewage treatment plants and garden enterprises and consulting with water treatment expert.
According to the connotation of the evaluation index and the evaluation standard, the actual condition of the pollutant treatment in the typical area is comprehensively considered, and the new pollutant efficiency of the sewage treatment facility is classified into four grades, namely low efficiency, medium efficiency, high efficiency and high efficiency.
Table 10 index System grading Standard
The acquisition of membership depends on raw data from the sewage treatment facility. And collecting pollutant reduction efficiency evaluation data of the sewage treatment facilities in the typical area, and acquiring raw data of the sewage treatment facilities. Dividing each secondary evaluation index into a qualitative index and a quantitative index, wherein the qualitative index obtains a membership value through an expert scoring method, and the quantitative index obtains the membership value through membership function calculation; and quantitatively processing quantitative indexes in the secondary evaluation indexes corresponding to the primary evaluation indexes including resource consumption, pollutant generation, environmental benefit and economic cost by using a membership function calculation method.
Firstly, obtaining a qualitative index membership value by adopting an expert scoring method, inviting an expert to score by referring to a grading standard, determining each index membership value, taking the automation level of a processing facility as an example, and if 1 expert has 1 to evaluate the processing facility as higher efficiency, dividing the processing facility by the total number of the experts to obtain the membership value of 0.1; the same 4 experts evaluate the performance as general performance, and the membership degree is 0.4; the 5 experts rated it as low efficacy with a membership of 0.5; its membership value R 1 = (0.5,0.4,0.1,0), the same can determine other qualitative rating index membership.
The quantitative index is based on fuzzy mathematical theory, and the membership value is determined by using a membership function calculation method. The original value X of each quantitative index is calculated according to the original data, and then normalized through the membership function. The original data comprise an inflow water quality index, an outflow water quality index and the like of the sewage treatment facility, so that the removal rate of conventional pollutants and the removal rate of new pollutants are calculated; the method comprises the steps of product yield, water consumption, raw material consumption, water consumption, wastewater production, production sewage discharge and the like, so as to calculate the wastewater production of unit products, pollutant production of unit products, water per ton investment cost, pollutant treatment cost per ton, raw material consumption of unit products and fresh water consumption of unit products.
Table 10 shows that the invention classifies the new pollutant efficiency of the sewage treatment facility into four classes, namely low efficiency, medium efficiency, high efficiency and extremely high efficiency. For quantitative indexes, the end point values of the dividing sections of the four grades are a, b and c in sequence from small to large, and the formed sections are < a, a-b, b-c and > c; the membership functions are constructed according to index system grading standards, and comprise larger membership functions and smaller membership functions.
For the larger membership functions, the membership functions are generally increasing, i.e. the larger a certain feature of an element, the larger the membership degree, when the evaluation index original value X is in the range of b-C, the larger the membership function C 1 B, C 2 C is; c when the original value X of the evaluation index is within the range of a-b 1 Is a, C 2 B is; the membership function f B1 (X) is as follows:
for the smaller membership functions, which generally decrease, i.e. the larger a certain feature of the element, the smaller the membership C of the smaller membership function when the evaluation index original value X is in the range of b-C 1 Is C, C 2 B is; c when the original value X of the evaluation index is within the range of a-b 1 B, C 2 A is a; the membership function f B2 (X) is as follows:
the larger function takes the removal rate of new pollutant A in the environmental benefit index as an example, and the membership function of the secondary index is to be determined as follows:
new contaminant a removal rate
Wherein n is 1 Concentration (ng/L), n of new contaminant A in influent to a wastewater treatment facility 2 Is the concentration (ng/L) of new pollutant A in the effluent of sewage treatment facilities.
The water output after the treatment of the treatment unit is evaluated, the threshold value of the membership function is determined by national standard, line standard and other data, and as shown in table 10, each interval is:>70，50<R≤70，20<r is less than or equal to 50 and less than or equal to 20; when new contaminant removal x=30, then C 1 ＝20％，C 2 ＝50％。
According to the above function f B1 (X) calculating the membership value of the removal rate of the new pollutant A, wherein the specific calculation process is as follows:
the membership value of the new contaminant A removal was thus [0.67,0.33,0,0], indicating that the new contaminant A removal was 67% likely to be of low efficacy and 33% likely to be of medium efficacy.
Taking the unit product wastewater production in the pollutant production index as an example, the membership function of the secondary index is to be determined as follows:
the unit product wastewater yield is evaluated, and the threshold value of the membership function is determined by national standard, line standard and other data, as shown in table 10, and each interval is as follows:<5，5≤R<10，10≤R<15, is more than or equal to 15; when the unit product wastewater production amount X=12t/t, the threshold value of the judging function is C 1 ＝15t/t、C 2 ＝10t/t。
By using the above function f B2 (X) calculating the membership value of the unit product wastewater production amount, wherein the specific calculation process is as follows:
the membership value of the wastewater yield per unit product thus obtained was [0.6,0.4,0,0], indicating that the wastewater yield per unit product was 60% likely to be of low efficiency and 40% likely to be of medium efficiency.
Similarly, the membership value of other quantitative indexes can be obtained through calculation according to the steps, the membership (R|ui) of the evaluated object under the single factor angle relative to the class fuzzy subset is finally determined, and then a fuzzy relation matrix is established, wherein specific data are shown in the following table 11.
TABLE 11 index values and membership degrees
(4) Comprehensive evaluation, determining pollutant reduction efficiency evaluation grade
And comprehensively evaluating according to the weight values and membership values of the first-level evaluation index and the second-level evaluation index to obtain a pollutant reduction efficiency evaluation result of the sewage treatment facility to be evaluated.
Performing secondary comprehensive evaluation by the secondary index weight value W' determined in the previous step, taking environmental benefit as an example, and comprehensively evaluating the result
Similarly, other first-level index comprehensive rating values can be calculated, as shown in the following table.
Table 12 secondary evaluation results
And then will be oneThe level index is used as single factor judgment of the efficiency evaluation target layer, and then the target layer is comprehensively evaluated to obtain the final processing facility efficiency evaluation result 
The pollutant abatement performance screening of typical regional sewage treatment facilities was ranked according to the calculation results, and the evaluation grade was determined, with the specific results shown in table 13.
TABLE 13 evaluation results of pollutant reduction efficacy of wastewater treatment facilities
From the results, it was found that the sewage treatment facility was evaluated to have a probability of 52% of pollutant reduction efficiency of low efficiency, 39.5% of medium efficiency, 6% of high efficiency, and 2.5% of extremely high efficiency. According to the principle of maximum membership, the "52%" is the maximum among four membership degrees, so the pollutant reduction efficiency of the sewage treatment facility is the "low efficiency", which indicates that the sewage treatment facility has a large improvement space for the cooperative reduction of characteristic new pollutants and conventional pollutants in the whole view, and needs to be improved.
From the above, according to the conventional pollutants and characteristic new pollutant types of the typical area and the traceable monitoring results, the method starts from evaluation indexes such as resource consumption, pollution generation, technical performance of processing facilities and the like, and firstly calculates related reduction evaluation indexes by using a FHW (fuzzy, gray and primitive space) method to evaluate the basic evaluation results and reliability of the indexes of each level, so that the reduction efficiency key evaluation indexes are preselected. And then organically combining an Analytic Hierarchy Process (AHP) with a fuzzy analysis process (FCE), further comparing importance among key indexes of all levels by using the analytic hierarchy process, constructing a judgment matrix, determining key index weights, determining evaluation grade membership by using the fuzzy analysis process, performing multistage fuzzy comprehensive evaluation, realizing unification of qualitative evaluation and quantitative evaluation, and further establishing a sewage treatment facility pollutant reduction efficiency evaluation system. The method realizes the preselection of efficiency evaluation indexes through a FHW method, overcomes the defects of the traditional analytic hierarchy process, increases the objectivity and the reliability of the analytic hierarchy process, determines the evaluation grade of the reduction efficiency of the treatment facility through membership calculation, and provides an evaluation system support for the cooperative reduction efficiency evaluation of the conventional pollutants and the new pollutants of the sewage treatment facility.
Therefore, the complete efficiency reduction evaluation system is constructed by the FHW method evaluation index preselection-analytic hierarchy process-fuzzy analysis method. More specifically, the invention uses FHW method to preselect the evaluation index and optimizes the analytic hierarchy process; the invention adopts an analytic hierarchy process-fuzzy comprehensive evaluation method, organically combines the analytic hierarchy process and the fuzzy comprehensive evaluation method, determines the weight of each evaluation index by using the analytic hierarchy process, comprehensively evaluates the evaluation results of each evaluation index by using fuzzy pattern recognition, complements the two, determines the environmental behavior condition according to the grade of each evaluation index, and jointly improves the reliability and the effectiveness of the evaluation. Moreover, as the evaluation method preselects a plurality of key reduction evaluation indexes, the cooperative reduction effect of the conventional pollutants and the characteristic new pollutants in the sewage treatment facility can be evaluated, and the energy consumption, the carbon resource utilization condition, the water balance condition and the like of the sewage treatment facility can be evaluated, so that the method meets the current double-carbon background.
The invention also provides a pollutant abatement efficacy evaluation system of a sewage treatment facility, comprising:
the evaluation index candidate module is used for screening and obtaining a first-level evaluation index and a second-level evaluation index from the candidate first-level evaluation index and the candidate second-level evaluation index through a FHW method;
The evaluation index weight determining module is used for determining weight values of the primary evaluation index and the secondary evaluation index;
the sewage treatment facility original data acquisition module is used for acquiring original data of the sewage treatment facility to be evaluated;
the multi-stage fuzzy comprehensive evaluation module is used for quantifying the original data through multi-stage fuzzy comprehensive evaluation to obtain membership values of evaluation indexes of each stage in each stage;
and the pollutant reduction efficiency evaluation module is used for obtaining the pollutant reduction efficiency evaluation result of the sewage treatment facility to be evaluated after comprehensive evaluation.
In a specific implementation, the present invention further provides a computer storage medium, where the computer storage medium may store a program, where the program may include some or all of the steps in each embodiment of the method and system for evaluating pollutant reduction efficiency of a sewage treatment facility provided by the present invention when the program is executed. It will be apparent to those skilled in the art that the techniques of embodiments of the present invention may be implemented in software plus a necessary general purpose hardware platform. Based on such understanding, the technical solutions in the embodiments of the present invention may be embodied in essence or what contributes to the prior art in the form of a software product, which may be stored in a storage medium, such as a ROM/RAM, a magnetic disk, an optical disk, etc., including several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute the method described in the embodiments or some parts of the embodiments of the present invention.
The same or similar parts between the various embodiments in this specification are referred to each other. In particular, for the device embodiments, since they are substantially similar to the method embodiments, the description is relatively simple, as far as reference is made to the description in the method embodiments.
The invention has been described in detail in connection with the specific embodiments and exemplary examples thereof, but such description is not to be construed as limiting the invention. It will be understood by those skilled in the art that various equivalent substitutions, modifications or improvements may be made to the technical solution of the present invention and its embodiments without departing from the spirit and scope of the present invention, and these fall within the scope of the present invention.
Claims (10)
1. A comprehensive multi-level sewage treatment facility pollutant reduction efficiency evaluation method is characterized by comprising the following steps:
s1: setting conventional pollutants and characteristic new pollutant reduction efficiency related indexes of a sewage treatment facility, wherein the conventional pollutants and characteristic new pollutants comprise candidate primary evaluation indexes and candidate secondary evaluation indexes; each candidate first-level evaluation index corresponds to a plurality of candidate second-level evaluation indexes; the candidate first-level evaluation indexes comprise resource consumption, pollutant generation, environmental benefit, economic cost, technical performance and management class;
S2: evaluating the candidate first-level evaluation index and the candidate second-level evaluation index by a FHW method to obtain an evaluation result; setting screening standards, and determining a first-level evaluation index and a second-level evaluation index according to the evaluation result and the screening standards;
s3: determining the weight value of the first-level evaluation index and the second-level evaluation index;
s4: constructing an index system grading standard to form a plurality of grades; acquiring original data of a sewage treatment facility to be evaluated; performing multi-level fuzzy comprehensive evaluation according to the original data and the index system grading standard to obtain membership values of evaluation indexes of each level in each level;
s5: and comprehensively evaluating according to the weight values and membership values of the first-level evaluation index and the second-level evaluation index to obtain a pollutant reduction efficiency evaluation result of the sewage treatment facility to be evaluated.
2. The method for evaluating the pollutant reduction efficiency of a sewage treatment facility according to claim 1, wherein the candidate secondary evaluation index corresponding to the resource consumption includes raw material consumption per unit product, fresh water consumption per unit product, electricity consumption per unit product; the candidate secondary evaluation indexes corresponding to the pollutant generation comprise the unit product wastewater generation amount, the unit product pollutant generation amount and the overall water balance condition of the treatment facility; the candidate secondary evaluation indexes corresponding to the environmental benefits comprise characteristic new pollutant removal rates and conventional pollutant removal rates; the candidate secondary evaluation indexes corresponding to the economic cost comprise ton water investment cost and ton water pollutant treatment cost; the candidate secondary evaluation indexes corresponding to the technical performance comprise the technical maturity, the removal pertinence of conventional pollutants and the removal pertinence of characteristic new pollutants; and the candidate secondary evaluation indexes corresponding to the management class comprise an automation level and a treatment facility energy-saving and carbon-reducing level.
3. The method for evaluating the pollutant reduction efficiency of a wastewater treatment facility according to claim 1, wherein the evaluating the candidate primary evaluation index and the candidate secondary evaluation index in step S2 by FHW method comprises:
s21: constructing a FHW expert consultation table, and grading the candidate primary evaluation index and the candidate secondary evaluation index for two rounds by a plurality of experts according to the FHW expert consultation table; averaging two groups of data obtained in the two rounds of scoring to form an evaluation matrix U;
u in the formula 1 ，u 2 ，...，u k Evaluating for a subject; (p) 1 ，a 1 )，(p 2 ，a 2 )，...，(p k ，a k ) Is a gray figure of merit, where p k Is the obvious goodness of the kth index, a k Potential goodness for the kth indicator; (q) 1 ，b 1 )，(q 2 ，b 2 )，…，(q k ，b k ) Is gray in degree, where q k B is the obvious degree of deterioration of the kth index k Potential inferior degree of the kth index;
s22: determining decision weight values fi of the plurality of experts;
s23: according to the evaluation matrix U and the decision weight fi of each expert, calculating to obtain each index item Y k Principal score value T k White superior-inferior ratio C k Gray superior-inferior ratio D k The method comprises the steps of carrying out a first treatment on the surface of the Wherein:
T k ＝Σu ki fi
wherein: u (u) ki As index item Y k I-th expert two-round scoring u for subject evaluation of (2) k Average value of (2); the index item Y k The method comprises the steps of respectively candidate first-level evaluation indexes and candidate second-level evaluation indexes;
Wherein: p is p k ＝Σp ki f i ，q k ＝Σq ki f i ，p ki Q ki Respectively index item Y k Apparent goodness p k And a degree of conspicuity q k An average of two rounds of scoring by the ith expert;
wherein: a, a k ＝Σa ki f i ，b k ＝Σp ki f i ，a ki B ki Respectively index item Y k Potential goodness a k And potential inferior degree b k The average of the scores of the ith expert in the two rounds.
4. The sewage treatment facility pollutant reduction performance evaluation method according to claim 3, wherein the evaluation result in step S2 comprises: the main grading values of the candidate first-grade evaluation indexes and the candidate second-grade evaluation indexes, the white superior-inferior ratio and the gray superior-inferior ratio; the screening criteria are: the main grading value is more than 80 points, and the white superior-inferior ratio and the gray superior-inferior ratio are both more than 1.
5. The method for evaluating the pollutant reduction efficiency of a sewage treatment facility according to claim 3, wherein step S22 comprises:
s221: determining all decision weight evaluation indexes as academic achievements in the aspects of relevant research, pollutant reduction evaluation, familiarity degree of the performance evaluation and caution attitude of the evaluation;
s222: assigning scores to each decision weight evaluation index of each expert, and then calculating to obtain a decision weight fi of each expert according to the weight value of each decision weight evaluation index and the following formula;
f i ＝λ 1 Ei+λ 2 Zi+λ 3 Ci+λ 4 Li
Wherein Ei, zi, ci, li sequentially and respectively represents the scoring values of four decision weight evaluation indexes, namely academic achievements of an ith expert in relevant research over 3 years, pollutant reduction evaluation, familiarity degree of the performance evaluation and caution attitude of the evaluation; lambda (lambda) 1 -λ 4 The weight values of the decision weight evaluation indexes are 0.20,0.15,0.35,0.30 in sequence.
6. The method for evaluating the pollutant reduction efficiency of a sewage treatment facility according to claim 1, wherein step S3 comprises:
s31: comparing and assigning the first-level evaluation index and the second-level evaluation index pairwise according to a 9-scale judging method;
s32: constructing a judgment matrix, and performing consistency inspection and normalization;
s33: and calculating to obtain the weight values of the first-level evaluation index and the second-level evaluation index.
7. The method for evaluating the pollutant reduction performance of a wastewater treatment facility according to claim 1, wherein the plurality of levels in step S4 comprises four levels of high performance, medium performance, and low performance;
in the step S4, performing multi-level fuzzy comprehensive evaluation, and obtaining membership values of each evaluation index in each level includes: dividing each secondary evaluation index into a qualitative index and a quantitative index, wherein the qualitative index obtains a membership value through an expert scoring method, and the quantitative index obtains the membership value through membership function calculation;
And quantitatively processing quantitative indexes in the secondary evaluation indexes corresponding to the primary evaluation indexes including resource consumption, pollutant generation, environmental benefit and economic cost by using a membership function calculation method.
8. The method for evaluating the pollutant reduction efficiency of a wastewater treatment facility according to claim 7,
the first-level evaluation index also comprises technical performance, and the second-level evaluation index corresponding to the technical performance is a qualitative index, and comprises technical maturity, pertinence for removing conventional pollutants and pertinence for removing characteristic new pollutants.
9. The method for evaluating the pollutant reduction efficiency of a wastewater treatment facility according to claim 7,
the end point values of the four-level dividing sections are a, b and c in sequence from small to large, and the formed sections are < a, a-b, b-c and > c;
the membership functions are constructed according to index system grading standards, and comprise larger membership functions and smaller membership functions;
for the larger membership function, when the original value X of the evaluation index is in the range of b-C, C of the larger membership function 1 B, C 2 C is; c when the original value X of the evaluation index is within the range of a-b 1 Is a, C 2 B is; the membership function f B1 (X) is as follows:
for the smaller membership function, when the original value X of the evaluation index is in the range of b-C, C of the smaller membership function 1 Is C, C 2 B is; c when the original value X of the evaluation index is within the range of a-b 1 B, C 2 A is a; the membership function f B2 (X) is as follows:
10. a pollutant abatement performance evaluation system for a wastewater treatment facility, comprising:
the evaluation index candidate module is used for screening and obtaining a first-level evaluation index and a second-level evaluation index from the candidate first-level evaluation index and the candidate second-level evaluation index through a FHW method;
the evaluation index weight determining module is used for determining weight values of the primary evaluation index and the secondary evaluation index;
the sewage treatment facility original data acquisition module is used for acquiring original data of the sewage treatment facility to be evaluated;
the multi-stage fuzzy comprehensive evaluation module is used for quantifying the original data through multi-stage fuzzy comprehensive evaluation to obtain membership values of evaluation indexes of each stage in each stage;
and the pollutant reduction efficiency evaluation module is used for obtaining the pollutant reduction efficiency evaluation result of the sewage treatment facility to be evaluated after comprehensive evaluation.
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