In the PPP project of rural sewage treatment, data mining technology is used to analyze the relationship of benefit and cost

Improvement of the quality of the water environment is the demand for the goal of building a moderately prosperous society in a comprehensive manner, the current rural areas due to the relatively weak economic base, rural sewage treatment investment is insufficient, resulting in poor quality of the water environment, the ecological environment is impaired, and may even lead to sanitation and health problems, rural sewage treatment has become a prominent short board of the comprehensive construction of a moderately prosperous society. Most of China’s rural areas are subject to regional backwardness, lack of funds, and rural sewage treatment specialization and economic efficiency is not high, relying on the local government financial investment or financial subsidies are obviously not enough [1–3]. Rural wastewater treatment is a quasi-public good, the private marginal benefit is less than the social marginal benefit, and the enterprise as a pursuit of economic efficiency, purely by the enterprise to provide high social public good low economic efficiency of rural wastewater treatment products lack of sufficient power and incentives. It can be seen that the government or the market alone can not provide rural sewage treatment products to achieve Pareto optimization [4–6]. In order to better promote the development of rural sewage treatment, China has made efforts to solve the problem of huge financial investment required for the full implementation of rural sewage treatment, accelerated the promotion of rural sewage treatment with the help of the power of social capital, solved the problems of large pressure of capital investment, insufficient technical force and unprofessional operation and maintenance in the rural sewage treatment, and vigorously implemented the PPP model of rural sewage treatment [7–9].

The level of cost-effectiveness and sustainability is a major factor that affects the development prospects of the wastewater treatment industry, especially the ability of wastewater treatment projects under the PPP model to operate according to the trends and performance envisioned by the policy. The cost-benefit analysis of wastewater treatment PPP projects in existing studies has been carried out from two aspects: cost control and benefit distribution [10–12]. On the one hand, considering the affordability of the people, the PPP project revenue is generally determined in accordance with the principle of capital preservation and micro-profit. Thus, in the case of relatively fixed revenue, it is necessary to start from the perspective of cost control, and save costs as much as possible while ensuring the quality of output [13–14]. On the other hand, in order to ensure the sustainability of the PPP project, the allocation of benefits is flexibly adjusted according to the changes in project cost inputs by establishing a dynamic benefit model for wastewater treatment PPP. However, the analysis of cost-effectiveness in existing studies focuses on individual projects and lacks the horizontal comparison of cost-effectiveness between wastewater treatment PPPs and wholly government-funded projects as well as the vertical comparison of cost-effectiveness within PPP projects [15–16]. Comparing wastewater treatment projects under the PPP model from a cost-benefit perspective, and evaluating the utility regarding cost inputs, benefit levels, and input-output efficiencies in the operation of the project are important means of exploring whether the PPP model can be long-lasting in the field of wastewater treatment [17–18]. The use of data mining technology for benefit-cost relationship analysis can timely identify the current PPP projects in the wastewater treatment industry in the operation and management of the problem, in order to provide an improvement plan to further optimize the application of the PPP model in wastewater treatment. Exploring the possible trends and potential laws affecting the operation of the project from a cost-benefit perspective can help form a theoretical basis for guiding the policy formulation of the choice of the operation mode for the construction of water treatment in local watersheds and towns and the construction of sewage treatment in beautiful villages [19–21].

Facing the increasingly serious rural sewage environmental problems, this paper takes the rural sewage treatment PPP project as a solution to the problem, tries to explore the benefit-cost relationship of the PPP project, and constructs an evaluation model corresponding to the cost and benefit. The data envelopment analysis (DEA) model is used for the eco-efficiency evaluation of incremental costs and benefits of rural sewage treatment PPP projects. Different rural wastewater treatment projects are set as the research object DMU, and the input and output index system should be established for DMU, specifying the input indexes mainly based on upfront cost and technology cost and the output indexes mainly based on economic benefit, social benefit and environmental benefit. The Charnes-Cooper transformation is performed to solve fractional planning. Finally, the incremental costs and benefits of building multiple PPP projects (DMUs) are entered into the final optimization model DCCR as input and output terms to complete the final solution. This paper provides an in-depth analysis of rural wastewater treatment projects in various regions of Anhui Province, China, to explore the cost and benefit performance of PPP projects there.

2

Rural Wastewater Treatment PPP Project

2.1

Rural Wastewater Treatment and PPP Projects

PPP is known as “government and social capital cooperation”, which refers to a cooperation mode in which the government and social capital jointly invest, construct, operate and manage public facilities or provide public services in a contractually agreed way [22]. The development of PPP mode can be traced back to Europe in the 1970s, and has been developed and widely used around the world. Development, it has been widely used globally and become an important cooperation method in the field of public services.

The PPP model emphasizes the marketization and professionalization of public asset management, making full use of social capital and market mechanisms to solve the problems of high pressure on government public finance, low investment efficiency and difficult project management, and to promote the construction and development of public service projects. Under the PPP model, the government provides support for the project in terms of land, policies, and approvals, while social capital is responsible for the design, construction, financing, operation, and maintenance of the project.

In terms of operation mode, PPP mode can be broadly categorized into four types, mainly Build-Operate-Transfer (BOT), Transfer-Operate-Transfer (TOT), Remodel-Operate-Transfer (ROT), Design-Operate-Transfer (DOT), and Design-Operate-Transfer (DOT). The classification of PPP projects can be divided into three parts: first, outsourcing projects, which mainly refers to the public sector dividing the whole project into several parts and outsourcing some or all of them to social capital to carry out operations. Second, concession type projects, mainly build-operate-transfer (BOT), transfer-operate-transfer (TOT), etc. The public sector will share the benefits of the project with the social capital, or even deliver it completely, while the risks of the project will be borne by the social capital and the Third, privatization projects, the private sector alone to invest all the funds to carry out the entire project construction and operation, and under the supervision and management of the public sector, the use of fees charged to the service recipients (the public or users), so as to obtain the project investment income, the construction of the project assets ultimately belong to the private capital alone possession. The PPP project operation process is shown in Figure 1.

Rural domestic sewage treatment PPP model, as the name suggests, is the use of PPP model, the treatment of rural domestic sewage, therefore, this paper considers that the rural domestic sewage treatment PPP model, refers to the government’s use of social capital, combined with the local natural resources, the use of reasonable treatment technology and equipment, the construction of the corresponding rural sewage treatment facilities, and through the franchising mode, to provide rural domestic sewage treatment Service. The government provides services for rural domestic wastewater treatment through PPP projects, and social capital is mainly responsible for design, financing, construction, operation, and transfer. The PPP model of rural domestic sewage treatment has the following advantages. 1)

Solving the problem of government financial insufficiency and effectively solving the shortcomings of rural sewage treatment.

2)

Improve the construction speed and utilize professional technicians to build sewage treatment facilities.

3)

Improve the sewage treatment rate.

4)

Improve the management level of sewage treatment facilities.

2.2

Full Life Cycle Costs of Rural Wastewater Treatment PPP Projects

2.2.1

Full project life cycle

The concept of full life cycle first came from the biological definition, for engineering projects, the full life cycle refers to the use of advanced information systems, such as computers, to coordinate and unify the concept of centralized management of all stages of the project from the inception to the end of life and so on.

The full life cycle of a construction project is to integrate the various stages of the construction process into a system of integrated management, in order to avoid the formation of the information gap between the construction parties in the process of cooperation and reduce the efficiency of the construction. The purpose of full life cycle management is to ensure that all stages of the project construction can meet the planning expectations, reduce the negative impacts caused by substandard construction, and ensure that the project benefits are maximized. Due to the involvement of a large number of participants, the construction period is long, the information flow generated by various departments at various stages may be duplicated or missing, however, in the full life cycle management system, through the timely feedback and adjustment of the information flow between the elimination of errors and omissions, reduce the probability of rework at a later stage, to achieve the purpose of cost savings.

Generally speaking, the entire life cycle of a construction project can be divided into the decision-making phase, implementation phase, and operation phase of the project.

The decision-making stage refers to the stage of pre-project planning and feasibility study demonstration to ensure that the project can meet the expected requirements.

The implementation phase can be divided into the pre-design preparation phase, the design phase, the construction phase, and the acceptance phase, in which the bidding work is scattered between the design preparation and the design phase.

The operation phase, in which the project has been put into operation, but the management, maintenance, and investment actions during operation still fall within the project’s full life cycle.

2.2.2

Theory of full life-cycle cost of construction projects

The definition of full life cycle cost LCC first originated in the United States.

For construction projects, full life cycle cost refers to the unified management of all costs and expenses of the project from the planning and construction, putting into use to the end-of-life stage, and its purpose is to control the unit cost of the project in the lowest range. Through the project life cycle cost management, planners can make reasonable estimation of the project life cycle cost in the early stage of project planning under the premise of full research and analysis, reduce the impact of uncertain factors on the cost, and do pre-control and control beforehand.

According to the type of cost, the entire life cycle cost of a construction project can be divided into three categories: construction cost, operation and maintenance cost, and disposal cost. Construction costs are all the costs incurred from the construction of a project until it is put into use; operation and maintenance costs refer to the management, maintenance, investment and other costs incurred during the use period of the project after it is completed and put into use; disposal costs refer to the future value of the project or the costs required to dispose of the project at the end of its expected life cycle, which can be positive or negative. Disposal costs mainly include sale value, demolition or site clearance costs and fees.

The full life-cycle cost of a project is calculated as in equation (1): 1 $LCC=CB+CM+CD$

Where, LCC - full life cycle cost of the project. CB

- construction cost.

CM

- maintenance cost.

CD

- disposal cost.

3

Rural wastewater management efficiency evaluation model

3.1

Model selection

In this paper, the data envelopment analysis (DEA) model is finally used for the eco-efficiency evaluation of the costs and benefits of rural wastewater treatment PPP projects [23].

According to the relevant literature, there are a variety of methods for evaluating efficiency, data envelopment analysis (DEA) is one of the most commonly used, which is suitable for evaluating the relative efficiency of a group of decision-making units (DMUs), i.e., a group of programs in which each program based on different inputs can be different outputs, through the inputs and outputs can be calculated by the relative efficiency of each program, using the principle of the program to explain the “input” data will have the “output” data, which will have the “output” data based on the “input” data to the program. Program “input” data will have “output” data, which “input” data for the input, that is, the implementation of the program should be consumed by the amount of energy, materials or other substances. The “output” is the amount of the corresponding product or factor obtained, e.g., the enterprise invests money and produces a product or receives a benefit.

3.2

Modeling

Referring to the working method of DEA to construct GE3 evaluation model, the specific process is as follows. 1)

Evaluation objective

The core objective is to analyze the eco-efficiency GE3 of incremental cost-effectiveness, and the corresponding evaluation objective is GE3.

2)

Selection of DMU

Based on the above, it is known that DMU is one of multiple decision-making programs, i.e., how to turn inputs into outputs for implementation. In this paper, the research object DMUs are different rural wastewater management PPP projects, with n rural wastewater management PPP projects for eco-efficiency evaluation, and use j to identify one of them. Setting DMU_j has n decision-making units, denoted as (j=1,2,…,n).

3)

Establishment of input-output indicator system

For the decision-making unit DMU to establish the input and output indicator system, clear input indicators and output indicators, these indicators are to express the relationship between the input and output of the DMU, so in order to guarantee the comparability of decision-making units, it is necessary to guarantee that all the projects have the same objectives, the external environment that can affect the results is consistent, and the number of relevant indicators is the same.

It is set that each DMU has the same m inputs (input items), input items i, i = 1,2,…,m, and the input vector is: 2 $x_{j} = {(x_{1 j}, x_{2 j}, \dots, x_{m j})}^{T} > 0, j = 1, 2, \dots, n$ x_ij denotes the amount of inputs of the j nd decision unit to the i rd type of input.

Set each decision unit to have the same s-item outputs (outputs) with outputs r, r = 1,2,…,s and an output vector of: 3 $y_{j} = {(y_{1 j}, y_{2 j}, \dots, y_{s j})}^{T} > 0, j = 1, 2, \dots, n$ y_ij denotes the output quantity of the j nd DMU for the ird type of output.

In order to harmonize all the inputs and outputs in the various DMUs, the process of program implementation is simply viewed as a production process with program inputs and outputs, and the input quantities are viewed as inputs and output quantities are viewed as outputs and are assigned weights, and the weight vectors of the inputs and outputs are set to be: 4 $v = {(v_{1}, v_{2}, \dots, v_{m})}^{T}, u = {(u_{1}, u_{2}, \dots, u_{s})}^{T}$ v_i is the weight of type i inputs and u_r is the weight of type r outputs.

Combined with the multi-input, single-output; multi-input, multi-output features of DEA, this paper divides the eco-efficiency index system of rural sewage treatment PPP project into two major aspects, the input indicators are the upfront cost and technology cost in incremental cost, and the output indicators are the economic, environmental and social benefits in incremental benefits.

To summarize this paper, there are two input item indicators and three output item indicators, the input weight coefficients correspond to two items and the output weight coefficients correspond to three items, and the specific decision-making units are expressed as follows:

4)

Selection of DEA model

According to the analysis of this paper on the incremental costs and incremental benefits of rural sewage treatment PPP project, it can be seen that the research program scenario is a fixed scale payoff scenario, so the CCR model is selected for evaluation, and the technical effectiveness and scale effectiveness of the eco-efficiency evaluation model of the incremental cost-effectiveness of the rural sewage treatment PPP project are also taken into account [24].

Based on the inputs and outputs, it can be seen that the combined value of inputs for decision unit j is $\sum_{i = 1}^{m} v_{i} x_{i j}$ the combined value of outputs is $\sum_{r = 1}^{s} u_{r} y_{r j}$ and the efficiency evaluation index for each decision unit DMU_j is: 5 $h_{j} = \frac{\sum_{r = 1}^{s} u_{r} y_{r j}}{\sum_{i = 1}^{m} v_{i} x_{i j}}, h_{j} \leq 1, j = 1, 2, \dots, t$

Where x_ij, y_ij for the incremental costs and incremental benefits of rural wastewater management PPP project, weight coefficients v and u for the variables, limiting all the h_j value (j = 1,2,⋯, n) does not exceed 1, that is, max h_j ≤ 1; the j₀ th decision-making unit of the efficiency evaluation, the larger the h_j0 indicates that the DUMj₀ can be used relative to the other decision-making units with fewer inputs to achieve a relatively large number of outputs. The relative efficiency optimization process of the j₀ th decision unit is the CCR evaluation model for: 6 $\begin{array}{l} \max h_{j_{0}} = \frac{\sum_{r = 1}^{s} u_{r} y_{r j_{0}}}{\sum_{i = 1}^{m} v_{i} x_{i j_{0}}} \\ s . t . & {\begin{array}{l} \frac{\sum_{r = 1}^{s} u_{r} y_{r j}}{\sum_{i = 1}^{m} v_{i} x_{i j}} \leq 1, j = 1, 2, \dots, n \\ v = {(v_{1}, v_{2}, \dots, v_{m})}^{T} \geq 0} \\ u = {(u_{1}, u_{2}, \dots, u_{s})}^{T} \geq 0 \end{array} \end{array}$

Since this is a fractional programming model, a Charnes-Cooper transformation is applied to this fractional programming in order to solve it. For this reason the order: 7 $t = \frac{1}{\sum_{i = 1}^{m} v_{i} x_{i j_{0}}}, μ_{r} = t μ_{r}, w_{r} = t v_{i}$

Then the model transforms to (P) : 8 $(P) {\begin{matrix} {maxh}_{j_{0}} = \sum_{r = 1}^{s} μ_{r} y_{r j_{0}} \\ s . t . {\begin{matrix} \sum_{r = 1}^{s} μ_{r} y_{r j} - \sum_{i = 1}^{m} w_{i} x_{i j} \leq 0, j = 1, 2, \dots, n \\ \sum_{i = 1}^{m} w_{i} x_{i j_{0}} = 1 \end{matrix} \\ μ_{r}, w_{i} \geq 0, i = 1, 2, \dots, m; r = 1, 2, \dots, s \end{matrix}$

Written in vector form there: 9 $(P) {\begin{matrix} \max h_{j_{0}} = μ^{T} Y_{0} \\ s . t . {\begin{matrix} μ^{T} Y_{j} - w^{T} X_{j} \leq 0 \\ w^{T} X_{0} = 1 \\ w, μ \geq 0 \end{matrix} j = 1, 2, \dots, n \end{matrix}$

The pairwise plan for plan P is D′CCR: 10 $(D' C C R) {s . t . {\begin{matrix} \min θ \\ \sum_{j = 1}^{n} λ_{j} x_{j} \leq θ x_{0} \\ \sum_{j = 1}^{n} λ_{j} y_{j} \geq y_{0} \\ λ_{j} \geq 0, j = 1, 2, \dots, n \\ θ U n r e s t r i c t e d \end{matrix}$

Further introduction of slack variable s⁺ and residual variable s⁻ reduces the above inequality constraint to an equality constraint, which can be changed to: 11 $(D C C R) {s . t . \begin{matrix} \min θ \\ {\begin{cases} \sum_{j = 1}^{n} λ_{j} x_{j} + s^{+} = θ x_{0} \\ \sum_{j = 1}^{n} λ_{j} y_{j} - s^{-} = y_{0} \\ λ_{j} \geq 0, j = 1, 2, \dots, n \\ θ U n r e s t r i c t e d s^{+} \geq 0, s^{-} \geq 0 \end{cases} \end{matrix}$

The incremental cost and incremental benefit of the construction of n rural wastewater management PPP project (DMU) as input and output terms are substituted into the final optimization model DCCR, and solved to find out θ, s⁺, and s⁻, θ to meet 0 ≤ θ ≤ 1. Currently, regarding the DEA modeling software, there are software such as EMS1, DEAP, DEAsolver, MYDEA, etc., which can be used to perform the solving [25].

5)

Evaluation analysis

According to the above model formula, set the above optimal solution as s^*−, θ*, θ maximum value when θ⁰ = 1. θ, s⁺, s value to determine the DEA under the CCR model effective then have the following.

(1)

When θ* = 1, and s^*+ = 0, s^*− = 0, then decision unit DMU_j0 is DEA effective, that is to say, the production activities of decision unit DMU_j0 are technically effective and scale effective at the same time. For the green eco-city construction project, the optimal incremental cost-effectiveness scheme of relatively minimal incremental cost and relatively maximum incremental benefit is realized.

(2)

When θ* = 1, s⁺ < 0 or s⁻ < 0 or both are greater than zero. At this point, the optimal value of the original linear programming $h_{j_{0}}^{*} = 1$ , called DMU_j0 for weak DEA effective, the case can not be achieved at the same time technically effective and scale effective. When the input s⁻ ≠ 0, and the output is insufficient amount s⁺ = 0, this result indicates that the green eco-urban area in the input is too much, and therefore guarantees the incremental benefits of the same situation, reduce the optimization of the incremental cost of inputs; on the contrary, the surface of the output is relatively insufficient, and in the case of guaranteeing that the incremental cost is unchanged, you can improve the incremental benefits of the space, to achieve the optimization of the green eco-urban area construction program.

(3)

If θ* < 1, decision unit DMU_j0 is not DEA effective. The scenario is neither scale effective nor technologically effective. It shows that there is room to optimize both the incremental costs and incremental benefits of green biopolis construction.

4

Evaluation of the rural wastewater management project in Anhui Province

This chapter will utilize the eco-efficiency evaluation model of rural wastewater treatment PPP projects constructed in this paper to conduct an in-depth analysis of rural wastewater treatment projects in various regions of Anhui Province, China, and explore the benefit-cost relationship therein.

4.1

Productivity index for rural wastewater treatment in Anhui Province

In the rural wastewater treatment project efficiency evaluation model, this paper establishes the corresponding output index system, in which the output indexes are economic benefits ECB, environmental benefits EVB, social benefits SOB. Using the panel data of the rural areas in 16 regions of the province in 2017-2023, the social benefit index of water pollution treatment in rural areas in Anhui Province was obtained, and the results are shown in Figure 2. From the specific data, the average value of social benefit of 16 rural areas in Anhui Province during 2017-2023 is 0.99, of which there are five rural sewage treatment social benefit is greater than 1, and the social benefit value of Maanshan is the largest, which is 1.613. The average value of economic benefit is 1.07, of which a total of eight areas in rural areas of sewage treatment benefit is greater than 1, and there are six areas of economic benefit. Lu’an is the region with the highest economic benefit of rural sewage treatment, reaching 1.206. As for the environmental benefit, its average value is 0.99, and the region with the highest environmental benefit is Huainan. It can be clearly seen that there are only four regions that can realize the growth of economic, environmental and social benefits at the same time, which are Huainan, Chuzhou, Lu’an, Ma’anshan and Tongling. On the contrary, there are Fuyang, Xuancheng, and Huangshan where economic, environmental, and social benefits have all declined.

4.2

Comparison of operating costs and benefits of rural wastewater treatment

In the previous section, this paper evaluates and analyzes the wastewater treatment productivity index of 16 rural areas in Anhui Province, in which the economic benefit ECB, environmental benefit EVB, and social benefit SOB of Huainan are 1.143, 1.044, and 1.083, respectively, which are all greater than the level of 1, and it is a rural area that adopts the rural wastewater treatment PPP project to carry out rural wastewater treatment activities. Xuancheng, on the other hand, is a rural area that does not adopt the rural wastewater treatment PPP project for rural wastewater treatment, and its economic benefit ECB, environmental benefit EVB, and social benefit SOB are 0.992, 0.946, and 0.846, respectively, all of which are less than the level of one. In order to further explore the impact of adopting rural wastewater treatment PPP projects on the costs and benefits of rural wastewater treatment, this section will take Huainan and Xuancheng as the research samples to conduct a cross-sectional comparative analysis of costs and benefits.

4.2.1

Cost analysis of sewage treatment

The total cost of sewage treatment includes depreciation costs of fixed assets, power costs, pharmaceutical costs, wages and benefits, repair and maintenance costs, financial costs, and other costs totaling 7 items. By calculating, comparing and analyzing the above 7 types of costs, the total annual operating costs and total unit costs can be summarized, and the proportion of each type of cost in the total cost can be more intuitively displayed. The wastewater treatment cost data of Xuancheng and Huainan are shown in Table 1. According to the table, the total cost of rural wastewater treatment in Xuancheng is 78.75 million yuan, of which the total cost of operation after deducting the total annual depreciation and financial expenses for the total annual operating costs (the cost of inputs in the annual operating process) of 57.77 million yuan, and the operating costs accounted for the proportion of the annual operating costs of 73.36%. While the total cost of rural wastewater treatment in Huaian is 52.58 million yuan, the operating cost is 29.07 million yuan, accounting for 55.29% of the total cost.

Table 1.

The cost of sewage treatment

Sequence	Item name	Unit	Xuancheng	Huainan
T1	Fixed asset depreciation cost	Ten thousand yuan	2067	1978
T2	Depreciation of buildings	Ten thousand yuan	554	793
T3	Equipment and installation depreciation	Ten thousand yuan	1523	1185
T4	Power cost	Ten thousand yuan	990	786
T5	Pharmacy cost	Ten thousand yuan	2535	803
T6	Wages and welfare costs	Ten thousand yuan	615	248
T7	Maintenance cost	Ten thousand yuan	780	660
T8	Financial cost	Ten thousand yuan	31	373
T9	Other expenses	Ten thousand yuan	857	410
T10	Annual assembly	Ten thousand yuan	7875	5258
T11	Operating cost	Ten thousand yuan	5777	2907

The comparison of unit operating costs between Huainan and Xuancheng is specifically shown in Figure 3. The total unit operating cost of Xuancheng is 2.684 yuan/ton, while that of Huainan is 2.402 yuan/ton, which is a smaller difference in the total operating cost. In terms of unit operating cost, Xuancheng needs to invest 1.97 yuan per ton of wastewater treated, while Huainan’s unit operating cost input is 1.305 yuan per ton. Whether in Xuancheng or Huainan, the three items of pharmaceuticals, depreciation and power costs account for a relatively high proportion of the total cost, which is the main cost indicator affecting the operating cost, and the three costs together account for 71.13% and 68.03%, respectively, which basically determines the total cost of the three cost levels.

In summary, Huainan, which adopts the rural sewage treatment PPP project for rural sewage treatment, invests 0.282 yuan/ton less in unit operating costs compared with Xuancheng, while Huainan invests more than Xuancheng in power costs, depreciation of fixed assets, repair and maintenance, and financial costs. This suggests that the rural wastewater treatment project in Huainan under the PPP model is not effective in operation, especially in the power cost, depreciation of fixed assets and other aspects of the space for further improvement.

4.2.2

Benefit analysis of sewage treatment

Sewage treatment revenue is affected by the unit price of sewage treatment and sewage treatment volume, the government and the operator in addition to the unit cost of sewage treatment in accordance with the operation of the agreement in addition to the unit price of sewage treatment, the operator in order to ensure reasonable profitability, but also need to agree with the government to the guaranteed amount of sewage treatment. Guaranteed volume of water that when the actual volume of sewage treatment is less than the guaranteed volume of water, the government needs to be in accordance with the guaranteed volume of water settlement of sewage treatment service fees, the actual volume of sewage treatment is greater than the guaranteed volume of water, it is necessary to settle in accordance with the actual volume of water treatment. The guaranteed volume of treatment often need to determine the break-even analysis in the capital preservation based on the guaranteed volume needs to be greater than or equal to the amount of capital preservation in order to make the operating unit profitable.

This paper uses gross profit to reflect the profitability of Xuancheng and Huainan rural wastewater treatment project, the profitability of the two specific as shown in Table 2. According to the table, the actual sewage treatment volume of Xuancheng and Huainan reached 2695 tons and 2195 tons, respectively, which exceeded the respective capital preservation volume of sewage treatment, and both achieved different degrees of profitability. The annual revenue of Xuancheng Rural Wastewater Treatment Project was 80.85 million yuan, and the gross profit from sales after deducting the annual treatment cost of 75.57 million yuan was 5.28 million yuan, with a gross profit margin of 6.53%. The gross profit margin of Huainan’s rural wastewater treatment project reached 18.63%, with a gross profit on sales of 12.27 million yuan. Compared with Huainan, Xuancheng’s profitability level is lower on the one hand because Xuancheng rural sewage treatment project did not use the PPP project mode, mainly operated by the institutions, the lack of management capacity resulting in high operating costs. On the other hand, it is because the government departments in the unit sewage treatment fee pricing to give institutions with less room for profit, the payment of fees to ensure that the normal operation of the sewage treatment project can be.

Table 2.

Benefits of sewage treatment

Item name	Unit	Xuancheng	Huainan
Fixed cost	Ten thousand yuan/year	2307	3688
Unit variable cost	Yuan/ton	1.948	0.761
Sales income price	Yuan/ton	3	3
Sewage treatment	Million tons/year	2380	1616
Actual sewage treatment	Million tons/year	2695	2195
Sewage treatment revenue	Ten thousand yuan/year	8085	6585
Sewage treatment cost	Ten thousand yuan/year	7557	5358
Sales gross profit	Ten thousand yuan/year	528	1227
Gross margin	Ten thousand yuan/year	6.53%	18.63%

4.3

Balancing the economic and societal benefits of rural wastewater management

The balance between economic and social benefits is the primary issue in the process of carrying out rural wastewater treatment PPP projects. In this section, we will discuss how to balance economic and social benefits in the process of building rural wastewater treatment PPP projects. The conditions for the balance of economic and social benefits are shown in Figure 4. To maximize the economic and social benefits of the sewage treatment project enterprise of the rural sewage treatment PPP project, it is necessary to control the construction scale in the planning of the sewage treatment project scale to achieve the breakeven point of 96,000 tons per day. Sewage treatment project in this production scale, will achieve the balance of costs and profits. 0.48 yuan / ton of sewage treatment price will make the enterprise will not get any economic profit to achieve the maximization of social benefits.

Assume that the demand curve D, happens to also intersect at the same time at the point. The government should regulate the enterprise production scale at 96,000 tons / day, the price is set at 0.48 yuan / ton. Through this price to inhibit sewage treatment enterprises, to achieve the goal of maximizing social benefits. Dalian City, sewage treatment demand is still relatively large, the demand curve is likely not just over the E point, but higher than the E point, then the price at this time will be higher than the average cost of rural sewage treatment project enterprises, enterprises to obtain a certain amount of economic profit, to achieve their own economic benefits. Demand curve if below the E point, then in a loss-making state. In order to protect the enthusiasm of enterprises to invest in rural sewage treatment projects, to ensure the normal operation of enterprises, the government must give enterprises appropriate subsidies. Rural sewage treatment project franchise price, is the government according to the specific treatment scale sewage treatment project cost composition, the real cost of the enterprise data grasp, in order to regulate sewage treatment project enterprise determined. This price is able to cover the normal cost of sewage treatment project enterprises, to ensure that enterprises can make a reasonable profit, and to protect the enthusiasm of enterprises to develop sewage treatment projects. At the same time, it is also necessary to prevent enterprises from pursuing economic benefits unilaterally without regard to the common benefits of society as a whole. The balance between economic and social benefits is achieved.

5

Conclusion

This study takes the rural wastewater treatment PPP project as the research theme, proposes to correspond to the whole life cycle of the project, and constructs a rural wastewater treatment efficiency evaluation model in order to quantify the benefit-cost relationship of the PPP project. Taking Anhui Province of China as the study area, the productivity index of rural wastewater treatment in 16 districts in the province is first analyzed. The average values of economic benefit ECB, environmental benefit EVB, and social benefit SOB among the 16 regions were 1.07, 0.99, and 0.99, respectively, corresponding to the highest regions of Lu’an, Huainan, and Ma’anshan, with the index values reaching 1.206, 1.044, and 1.613. Selected 16 areas in Huainan and Xuancheng for a step-by-step open that rural sewage treatment operating costs and benefits of the comparison, in which Huainan for the use of rural sewage treatment PPP project areas, while Xuancheng is still maintaining the traditional rural sewage treatment methods. Through comparison, it can be learned that Xuancheng rural sewage treatment annual operating costs accounted for 73.36% of the operating costs, reaching 57.77 million yuan. The operating cost of Huainan is 29.07 million yuan, accounting for 55.29% of the total cost. In terms of sewage treatment benefits, the gross profit rate of rural sewage treatment project in Huainan reached 18.63%, and the gross profit from sales was 12.27 million yuan, higher than Xuancheng’s gross profit rate and gross profit from sales of 12.1% and 6.99 million yuan. Obviously, the rural sewage treatment PPP project is relatively more cost-efficient than the traditional project. The PPP project is used as the core method of the main village sewage treatment, and the balance of its economic and social benefits is discussed. When the production scale of rural sewage treatment is at 96,000 tons/day and the price is set at 0.48 yuan/ton, the goal of maximizing social benefits can be achieved and the balance between economic and social benefits can be maintained.

Language:: English

Publication timeframe:: 1 times per year
Journal Subjects:: Life Sciences, Life Sciences, other, Mathematics, Applied Mathematics, General Mathematics, Physics, Physics, other

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In the PPP project of rural sewage treatment, data mining technology is used to analyze the relationship of benefit and cost

Xiaochi Yang

Published Online: Mar 19, 2025

Received: Nov 10, 2024

Accepted: Feb 17, 2025

DOI: https://doi.org/10.2478/amns-2025-0446

KeywordsPPP project, Rural wastewater treatment, Project life cycle, Data mining techniques, DEA modeling

© 2025 Xiaochi Yang, published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Keywords
PPP project, Rural wastewater treatment, Project life cycle, Data mining techniques, DEA modeling