Optimization method of rural domestic sewage treatment mode based on improved spatial clustering algorithm

Abstract

The present invention discloses a method for optimizing rural domestic sewage treatment mode based on an improved spatial clustering algorithm. First, the cluster center coordinate calculation formula is corrected by the village population and terrain elevation to generate alternative schemes for rural domestic sewage treatment mode; secondly, the bill of materials of each alternative sewage treatment facility is analyzed to analyze its environmental impact over the entire life cycle; thirdly, the initial cost, construction cost, operation cost and abandonment cost of the sewage treatment facility are calculated; finally, the objective function is constructed based on the environmental impact potential value and treatment cost over the entire life cycle, and multi-objective optimization is performed on each treatment mode alternative scheme to obtain the optimal sewage treatment mode under different scenario conditions. The present invention can be used to scientifically determine the spatial layout, treatment scale and treatment process of rural domestic sewage treatment facilities, and can be promoted and applied in the preparation of special plans for rural domestic sewage treatment and comprehensive rural environmental improvement plans.

Description

Technical Field

[0001] The invention relates to a rural domestic sewage treatment mode optimization method based on a spatial clustering improved algorithm, and belongs to the technical field of environmental management. Background Art

[0002] As the degree of agricultural modernization continues to improve, rural water environment problems are becoming increasingly prominent. At the same time, affected by the dual structure of urban and rural economic and social development, rural water environment infrastructure and governance capabilities are relatively weak. Rural water ecological environment safety and ecological protection issues are the weak links in rural environmental protection work and the key constraints on the development of new rural construction. Therefore, strengthening the construction of rural domestic sewage treatment facilities has become an important part of my country's comprehensive rural environmental governance and ecological environment construction.

[0003] Rural domestic sewage treatment modes mainly include piped treatment, centralized treatment and decentralized treatment. Reasonable determination of sewage treatment modes and treatment facility scale is an important prerequisite for maximizing the environmental and economic benefits of rural domestic sewage. At present, most related studies take construction investment and operation costs as considerations, and rarely take the environmental impact of the entire process of sewage facility construction and operation into decision-making. Therefore, it is necessary to comprehensively consider factors such as environmental impact and treatment costs throughout the life cycle, reasonably determine the spatial layout, treatment scale and treatment process of rural domestic sewage treatment facilities, improve the scientific nature of the decision-making process of rural domestic sewage treatment modes, and maximize the environmental and economic benefits of rural domestic sewage. Summary of the invention

[0004] Purpose of the invention: In order to overcome the shortcomings of the prior art, the present invention provides a rural domestic sewage treatment model optimization method based on a spatial clustering improved algorithm, which improves the scientific nature of the rural domestic sewage treatment model decision-making process, and maximizes the environmental and economic benefits of rural domestic sewage treatment. It can be promoted and applied in the preparation of special plans for rural domestic sewage treatment and comprehensive rural environmental improvement plans.

[0005] Technical solution: To solve the above technical problems, the present invention provides a rural domestic sewage treatment mode optimization method based on a spatial clustering improved algorithm, comprising the following steps:

[0006] (1) A spatial clustering algorithm is used to generate a variety of rural domestic sewage spatial layout plans, and combined with a variety of sewage treatment processes to form several alternative treatment model plans;

[0007] (2) Conduct an inventory analysis of the sewage treatment facilities of each alternative, establish a sewage treatment facility life cycle assessment model, and calculate the environmental impact potential over the entire life cycle;

[0008] (3) Calculate the initial cost, construction cost, operating cost, and abandonment cost of each alternative plan, construct a life cycle cost model for sewage treatment facilities, and calculate the sewage treatment cost over the entire life cycle;

[0009] (4) The objective function is constructed based on the environmental impact potential of the entire life cycle and the treatment cost, and multi-objective optimization is performed on the alternative treatment modes to obtain the optimal sewage treatment mode under different scenario conditions.

[0010] Preferably, the step (1) uses an improved k-means algorithm for spatial clustering, and the specific improvement process is as follows:

[0011] First, construct cluster y as follows: j Population and terrain elevation weight factors of each village:

[0012]

[0013]

[0014] Where P xi * is the population weight factor of village xi; P xi is the population of village xi; P min is the cluster y j The minimum population of each village; P max is the cluster y j The maximum population of each village; α P P xi * The lower limit of α P ∈ (0,1); CV P is the cluster y j The coefficient of variation of the population of each village indicates the degree of dispersion of the population; P t is the threshold value of the coefficient of variation of population size, ranging from 10% to 20%; Z xi * is the village terrain elevation weight factor; Z xi is the terrain elevation of village xi; Z min is the cluster y j Minimum elevation of each village terrain; Z max is the cluster y j The maximum elevation of each village terrain; α Z Z xi * The lower limit of α Z ∈(0,1);CV Z is the cluster y j The coefficient of variation of the terrain elevation of each village indicates the degree of dispersion of the terrain elevation; Z tis the threshold of terrain elevation variation coefficient, which is 10% to 20%.

[0015] α in formula (1) P , is to prevent the emergence of the village P with the smallest population xi * When α is zero, the denominators of formulas (3) and (4) are zero. Z , is to avoid the village Z with the lowest terrain elevation xi * is equal to zero, resulting in the horizontal and vertical terms of village xi in formula (3) and formula (4) being zero.

[0016] At the same time, in order to avoid the differences in population size or terrain height differences among villages in the study area, the P xi * and Z xi * The role of P is to use piecewise function to calculate P xi * and Z xi * When the coefficient of variation of population or terrain elevation in the study area is less than or equal to a certain threshold, it means that the population difference of villages in the area is small or the terrain is flat. xi * or Z xi * =1.0, which is equivalent to ignoring the influence of population or terrain. When the coefficient of variation of population or terrain elevation in the study area is greater than a certain threshold, the normalized function is used to calculate P xi * or Z xi * .

[0017] From the perspective of reducing investment costs and operating costs and reducing pipe network leakage, sewage treatment facilities should be located near villages with large populations and low terrain elevations as much as possible. Therefore, the following formula is used to modify the cluster y j The center coordinates calculation method is:

[0018]

[0019]

[0020] In the formula, X yj and Y yj They are the corrected cluster y j The horizontal and vertical coordinates of the center; X xi and Y xi Village x i The horizontal and vertical coordinates of jThe number of villages.

[0021] Finally, the spatial clustering of sewage treatment facilities is completed according to the remaining steps of the k-means algorithm.

[0022] Preferably, the multiple sewage treatment processes in step (1) include mainstream rural biological sewage treatment processes such as anaerobic-anoxic-aerobic method AAO, integrated sewage treatment MBR, sequencing batch activated sludge method SBR and composite biological filter.

[0023] Preferably, the inventory analysis in step (2) is to investigate and collect data on raw materials and energy consumed and air pollutants, solid wastes and water pollutants emitted during the entire life cycle of the sewage treatment facility.

[0024] Preferably, the sewage treatment cost LCC over the entire life cycle in step (3) is C1+C2+C'3+C'4, where C1 is the initial cost, RMB; C2 is the construction cost, RMB; C3' is the total operating cost of the sewage treatment facility during its life cycle, RMB; and C4' is the waste cost converted into current cost, RMB; wherein:

[0025]

[0026]

[0027] Where, C3 is the annual operating cost, RMB; C4 is the abandonment cost, RMB; r is the discount rate, %; N l is the life span of sewage treatment facilities, years.

[0028] Preferably, in step (4), the coordinates of the center points of each village are obtained according to the administrative division map of the study area, a series of numbers of sewage treatment facilities to be built are set as the number of clusters k, and the k-means algorithm is used for spatial clustering to generate multiple rural domestic sewage spatial layout plans. The centroid of each cluster generated by each spatial layout plan is used as the proposed site for the sewage treatment facility. The population of each village corresponding to each cluster is counted, the corresponding rural domestic sewage discharge is calculated, the construction scale of the sewage treatment facility is determined, and the distance from the village to the sewage treatment facility is measured and used as the length of the pipeline network for calculating the environmental impact potential and the sewage treatment cost.

[0029] Preferably, the method for determining the best sewage treatment mode in step (4) is: normalizing the environmental impact potential and treatment cost of the entire life cycle, and the calculation formula is as follows:

[0030]

[0031]

[0032] Where, EIP* and LCC * are the normalized environmental impact potential and governance cost respectively; EIP and LCC are the full life cycle environmental impact potential and governance cost respectively; EIP max and LCC max are the maximum values ​​of environmental impact potential and governance cost, EIP min and LCC min are the minimum values ​​of environmental impact potential and governance cost respectively;

[0033] The normalized environmental impact potential EIP of each alternative plan * and governance cost LCC * and the number of sewage treatment facilities N w Perform nonlinear fitting to obtain the environmental impact potential objective function f1(N w ) and governance cost objective function f2(N w ).

[0034] The weighted summation method is used to transform the multi-objective optimization problem into a single-objective optimization problem. The objective function of a sewage treatment process is as follows:

[0035] min F(x)=ω1f1(N w )+ω2f2(N w ) (9)

[0036] ω1+ω2=1 (10)

[0037] Where N w is the number of sewage treatment facilities, N w ∈[1,N v ],N v is the number of villages; ω1 and ω2 are the weight coefficients of the environmental impact potential and governance cost objective functions, representing the importance of the two, ω1, ω2∈[0,1];

[0038] By setting the weight coefficients ω1 and ω2 of multiple objective functions, a multi-objective optimization method (e.g., sequential quadratic programming) is used to solve the optimal solution of the objective function with the minimum environmental impact and the lowest governance cost under different weight coefficient combinations, that is, the optimal number of sewage treatment facilities and sewage treatment process, as the optimal sewage treatment mode. When using the spatial clustering algorithm to generate alternative plans for the spatial layout of sewage treatment facilities, the influence of village population and terrain elevation factors on the clustering results is comprehensively considered. By setting weighting factors and correcting the calculation formula of cluster center coordinates, the disadvantage of using only spatial distance as the criterion for cluster center is overcome, so that the clustering results of the spatial layout of sewage treatment facilities are more reasonable.

[0039] Beneficial effect: Compared with the prior art, the rural domestic sewage treatment mode optimization method based on the improved spatial clustering algorithm of the present invention adopts the improved k-means spatial clustering algorithm to generate the rural domestic sewage spatial layout plan, combines the full life cycle environmental impact assessment technology and the sewage treatment cost accounting method, constructs the objective function with the full life cycle environmental impact potential and the treatment cost, and performs multi-objective optimization on the alternative schemes of each treatment mode to obtain the optimal sewage treatment mode under different scenario conditions, thereby improving the scientific nature of the decision-making process of the rural domestic sewage treatment mode, and maximizing the environmental and economic benefits of rural domestic sewage treatment. It can be promoted and applied in the preparation of special plans for rural domestic sewage treatment and comprehensive rural environmental improvement plans. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] Figure 1 This is the town-level administrative division map of District A;

[0041] Figure 2 This is the spatial distribution map of villages in Area A;

[0042] Figure 3 This is the layout diagram of rural sewage treatment facilities in Area A (taking the example where the number of sewage treatment facilities are 1, 5, 10, and 20 respectively). DETAILED DESCRIPTION

[0043] The present invention will be further described below in conjunction with the accompanying drawings.

[0044] This embodiment takes a district (District A) under the jurisdiction of a city in eastern China as an example to perform an optimization analysis of the rural domestic sewage treatment management model based on the improved spatial clustering algorithm. There are 1,150 natural villages in District A.

[0045] The rural domestic sewage treatment mode optimization method based on the spatial clustering improved algorithm includes the following steps:

[0046] (1) Determine alternative solutions for rural domestic sewage treatment models

[0047] According to the spatial distribution map of villages in Area A ( Figure 2 ) obtains the geographic coordinates of 1150 natural villages, sets a series of numbers of proposed sewage treatment facilities (1, 5, 10, 20, 50, 100, 200, 500, 1150) as the cluster number k, and uses the improved k-means algorithm for spatial clustering to generate multiple rural domestic sewage spatial layout plans, such as Figure 3 As shown in the figure. The centroid of each cluster generated by each spatial layout plan is used as the proposed construction site of the sewage treatment facility. The population of the village corresponding to each cluster is counted, the corresponding rural domestic sewage discharge is calculated, the construction scale of the sewage treatment facility is determined, and the distance from the village to the sewage treatment facility is measured and used as the length of the pipeline network.

[0048] According to the administrative division map of the study area, the coordinates of the center points of 1150 natural villages were obtained, and a series of numbers of proposed sewage treatment facilities were set as the number of clusters k. The calculation method of cluster center coordinates was improved, and the improved k-means algorithm was used for spatial clustering to generate multiple rural domestic sewage spatial layout plans. The specific improvement process is as follows:

[0049] First, calculate each cluster y as follows: j Population and terrain elevation weight factors of each village:

[0050]

[0051]

[0052] Where P xi * is the population weight factor of village xi; P xi is the population of village xi; P min is the cluster y j The minimum population of each village; P max is the cluster y j The maximum population of each village; α P P xi * The lower limit of CV is 0.1; P is the cluster y j The coefficient of variation of the population of each village indicates the degree of dispersion of the population; P t is the population variation coefficient threshold, which is 15%; Z xi * is the village terrain elevation weight factor; Z xi is the terrain elevation of village xi; Z min is the cluster y j Minimum elevation of each village terrain; Z max is the cluster y j The maximum elevation of each village terrain; α Z Z xi * The lower limit of CV is 0.1; Z is the cluster y j The coefficient of variation of the terrain elevation of each village indicates the degree of dispersion of the terrain elevation; Z t is the threshold value of the coefficient of variation of terrain elevation, which is taken as 15%;

[0053] The clustering y is modified using the following formula j The center coordinates calculation method is:

[0054]

[0055]

[0056] Where, X yj and Y yj They are the corrected cluster y j The horizontal and vertical coordinates of the center; X xi and Y xi Village x i The horizontal and vertical coordinates of the center, for example, can be the coordinates of the location of the village committee; m is the cluster y j Number of villages;

[0057] Finally, the spatial clustering of sewage treatment facilities is completed according to the remaining steps of the k-means algorithm.

[0058] Multiple rural domestic sewage spatial layout plans are combined with a variety of sewage treatment processes (AAO, MBR, SBR and composite biological filter) to form several alternative treatment model options.

[0059] (2) Calculation of the environmental impact potential over the entire life cycle

[0060] An inventory analysis is conducted for each alternative sewage treatment facility, including investigation and collection of raw materials, energy consumed, and air pollutants, solid waste, and water pollutants emitted during the entire life cycle of the sewage treatment facility. Data sources include various statistical yearbooks and reports, laboratory test data, books or papers, feasibility reports and design materials, and relevant environmental data manuals.

[0061] The construction phase inventory includes building materials (metal pipes, cement, bricks, sand and gravel, etc.), equipment (pumps, blowers, mixers, etc.), energy (electricity, oil, coal) and resources (water) consumed during the transportation of materials and equipment and the construction process, and waste gases (CO2, SO2, NO x , CO, particulate matter, dust), wastewater (COD, TN, TP, SS, sulfide), solid waste (excavated earth, slag, inorganic waste).

[0062] The operation phase inventory includes energy (electricity) and chemical agents (sodium acetate, methanol, PAC, PAM, lime, chlorine, etc.), CO2, H2S waste gas and solid waste such as screenings and sludge.

[0063] The scrapping stage inventory includes waste gases (CO2, SO2, NO x , CO, particulate matter, dust), wastewater (COD, TN, TP, SS, sulfide), solid waste (concrete, bricks, slag).

[0064] The life cycle impact assessment software Open-LCA was used, with the help of the environmental load database ecoinvent and the CML2001 assessment method, and the existing technology was used to establish a life cycle assessment model for rural domestic sewage treatment facilities. The environmental impacts of the entire life cycle were divided into three categories: resource consumption (non-biological resources and biological resources), environmental pollution (greenhouse effect, ozone layer depletion, human toxicity, ecotoxicity, acidification, eutrophication) and damage.

[0065] According to the construction scale of sewage treatment facilities and the length of pipe network laying of each alternative plan, the constructed life cycle assessment model is used to calculate the environmental impact potential of the whole life cycle according to the steps of characterization, standardization, weighting, etc. First, the characterization model is used to obtain the quantified environmental impacts of various types, and then the characterization results of each environmental impact are compared with the standardized reference to obtain the standardized environmental impact. The standardized reference is generally the total amount of contributing substances under each environmental catalog of a specific country or region. Finally, the weighting factor is applied to combine the standardized results of various environmental impacts into a "single value" as the environmental impact potential of the whole life cycle.

[0066] (3) Calculate the cost of sewage treatment over the entire life cycle

[0067] The initial cost includes the cost of construction permit, engineering design and planning, engineering site selection and preparation, and bidding; the construction cost includes equipment purchase and installation costs, engineering and pipeline construction and construction costs, land costs (purchase) and all other entrusted costs; the operating cost includes system and equipment maintenance, staff salaries, chemical input and sludge treatment costs; the abandonment cost includes the cost of project demolition and treatment, environmental remediation, and resource recovery.

[0068] The discount rate is used to convert future costs such as operating costs and waste costs into current costs, so that the costs incurred in different periods can be directly compared. The calculation formula is:

[0069]

[0070]

[0071] In the formula, C3 is the annual operating cost, RMB; C3' is the total operating cost of the sewage treatment facility during its life cycle, RMB; C4 is the abandonment cost, RMB; C4' is the abandonment cost converted into current cost, RMB; r is the discount rate, %; N l is the life span of sewage treatment facilities, years.

[0072] The formula for calculating the life cycle cost is:

[0073] LCC=C1+C2+C'3+C'4 (7)

[0074] In the formula, C1 is the initial cost, RMB; C2 is the construction cost, RMB; LCC is the sewage treatment cost over the entire life cycle, RMB.

[0075] (4) Multi-objective optimization of governance model alternatives

[0076] The full life cycle environmental impact potential and governance cost are normalized and the calculation formula is as follows:

[0077]

[0078]

[0079] Where, EIP * and LCC * are the normalized environmental impact potential and governance cost respectively; EIP and LCC are the full life cycle environmental impact potential and governance cost respectively; EIP max and LCC max are the maximum values ​​of environmental impact potential and governance cost, EIP min and LCC min are the minimum values ​​of environmental impact potential and governance cost respectively.

[0080] The normalized environmental impact potential EIP of each alternative plan * and governance cost LCC * and the number of sewage treatment facilities N w Perform nonlinear fitting to obtain the environmental impact potential objective function f1(N w ) and governance cost objective function f2(N w ).

[0081] The weighted summation method is used to transform the multi-objective optimization problem into a single-objective optimization problem. The objective function of a sewage treatment process is as follows:

[0082] min F(x)=ω1f1(N w )+ω2f2(N w ) (10)

[0083] ω1+ω2=1 (11)

[0084] Where N w is the number of sewage treatment facilities, N w ∈[1,1150]; ω1 and ω2 are the weight coefficients of the environmental impact potential and governance cost objective functions, respectively, representing the importance of the two, ω1,ω2∈[0,1].

[0085] By setting the weight coefficients ω1 and ω2 of multiple objective functions, a multi-objective optimization method (for example, sequential quadratic programming) is used to solve the optimal solution of the objective function with the smallest environmental impact and the lowest treatment cost under different weight coefficient combinations, that is, the optimal number of sewage treatment facilities and sewage treatment process, as the optimal sewage treatment model.

[0086] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principle of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. A rural domestic sewage treatment mode optimization method based on spatial clustering improved algorithm, characterized in that: The following steps are involved: (1) Using the improved spatial clustering algorithm to generate a variety of rural domestic sewage spatial layout plans, and combining them with a variety of sewage treatment processes to form several alternative treatment model plans; (2) Conduct an inventory analysis of the sewage treatment facilities of each alternative, establish a sewage treatment facility life cycle assessment model, and calculate the environmental impact potential over the entire life cycle; (3) Calculate the initial cost, construction cost, operating cost, and abandonment cost of each alternative plan, construct a life cycle cost model for sewage treatment facilities, and calculate the sewage treatment cost over the entire life cycle; (4) The objective function is constructed based on the environmental impact potential value and treatment cost of the entire life cycle, and multi-objective optimization is performed on the alternative treatment modes to obtain the optimal sewage treatment mode under different scenario conditions; In the step (1), the coordinates of the center points of each village are obtained according to the administrative division map of the study area, a series of numbers of sewage treatment facilities to be built are set as the cluster number k, and the improved k-means algorithm is used for spatial clustering to generate multiple rural domestic sewage spatial layout plans. The specific improvement process is as follows: First, construct the weight factors of village population and terrain elevation as follows: Where P xi * is the weight factor of the village population; P xi is the population of village xi; P min is the minimum population of each village; P max is the maximum population of each village; α P P xi * The lower limit of α P ∈(0,1); CV P is the coefficient of variation of the population of each village, indicating the degree of dispersion of the population; P t is the threshold value of the coefficient of variation of population size, ranging from 10% to 20%; Z xi * is the village terrain elevation weight factor; Z xi is the terrain elevation of village xi; Z min is the minimum value of terrain elevation of each village; Z max is the maximum value of terrain elevation of each village; α Z Z xi * The lower limit of α Z ∈(0,1); CV Z is the coefficient of variation of the terrain elevation of each village, indicating the degree of dispersion of the terrain elevation; Z t is the threshold value of the coefficient of variation of terrain elevation, which is 10% to 20%; The village x is modified by the following formula i To cluster center y j The Euclidean distance is: In the formula, d(x i ,y j ) is the modified village x i To cluster center y j The Euclidean distance of x i 1 For the village x i The horizontal axis of i 2 For the village x i The vertical coordinate; y j 1 is the cluster center y j The horizontal axis of y j 2 is the cluster center y j The vertical coordinate of Finally, the spatial clustering of sewage treatment facilities is completed according to the remaining steps of the k-means algorithm; The sewage treatment cost of the whole life cycle in step (3) LCC=C1+C2+C'3+C'4, C1 is the initial cost, RMB; C2 is the construction cost, RMB; C3' is the total operating cost of the sewage treatment facility during its life cycle, RMB; C4' is the waste cost converted into current cost, RMB; where: Where, C3 is the annual operating cost, RMB; C4 is the abandonment cost, RMB; r is the discount rate, %; N l is the life span of sewage treatment facilities, years; The method for determining the optimal sewage treatment mode in step (4) is: normalizing the environmental impact potential and treatment cost of the entire life cycle, and the calculation formula is as follows: Where, EIP * and LCC * are the normalized environmental impact potential and governance cost respectively; EIP and LCC are the full life cycle environmental impact potential and governance cost respectively; EIP max and LCC max are the maximum values ​​of environmental impact potential and governance cost, EIP min and LCC min are the minimum values ​​of environmental impact potential and governance cost respectively; The normalized environmental impact potential EIP of each alternative plan * and governance cost LCC * and the number of sewage treatment facilities N w Perform nonlinear fitting to obtain the environmental impact potential objective function f1(N w ) and governance cost objective function f2(N w ); The weighted summation method is used to transform the multi-objective optimization problem into a single-objective optimization problem. The objective function of a sewage treatment process is as follows: minF(x)=ω1f1(N w )+ω2f2(N w ) (8) ω1+ω2=1 (9) Where N w is the number of sewage treatment facilities, N w ∈[1,N v ],N v is the number of villages; ω1 and ω2 are the weight coefficients of the environmental impact potential and governance cost objective functions, representing the importance of the two, ω1, ω2∈[0,1]; By setting the weight coefficients ω1 and ω2 of multiple objective functions, a multi-objective optimization method is used to solve the optimal solution of the objective function with the smallest environmental impact and the lowest treatment cost under different weight coefficient combinations, that is, the optimal number of sewage treatment facilities and sewage treatment process, as the optimal sewage treatment model.

2. The rural domestic sewage treatment mode optimization method based on the spatial clustering improved algorithm according to claim 1 is characterized by: The various sewage treatment processes in step (1) include anaerobic-anoxic-aerobic method AAO, integrated sewage treatment MBR, sequencing batch activated sludge method SBR and composite biological filter.

3. The rural domestic sewage treatment mode optimization method based on the spatial clustering improved algorithm according to claim 1 is characterized by: The inventory analysis in step (2) is to investigate and collect data on the raw materials and energy consumed and the air pollutants, solid wastes and water pollutants emitted during the entire life cycle of the sewage treatment facility.

4. The rural domestic sewage treatment mode optimization method based on the spatial clustering improved algorithm according to claim 1 is characterized by: In the step (4), each cluster centroid generated by each spatial layout plan is used as the proposed construction site of the sewage treatment facility, the population of the village corresponding to each cluster is counted, the corresponding rural domestic sewage discharge is calculated, the construction scale of the sewage treatment facility is determined, and the distance from the village to the sewage treatment facility is measured and used as the length of the pipeline network to calculate the environmental impact potential and sewage treatment cost.

Images