Study on the evaluation system and risk factor traceability of receiving water body

Yang Qiu; Xiaoming Ren; Zixuan Wang; Yukun Zhou

doi:10.1515/geo-2022-0580

Article Open Access

Study on the evaluation system and risk factor traceability of receiving water body

Yang Qiu , Xiaoming Ren , Zixuan Wang and Yukun Zhou

Published/Copyright: December 15, 2023

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From the journal Open Geosciences Volume 15 Issue 1

Abstract

The risk factor of the receiving water body is one of the important factors that affect the self-purification ability of the water body. Analyzing the concentration and removal rate of the target substances such as suspended solid (SS), chemical oxygen demand (COD), total nitrogen (TN), and total phosphorus (TP) in the receiving water body during the life cycle can trace the risk factor. Based on this, this article takes a sewage treatment plant and its receiving water body in Nanjing as the research object, sets up five sampling points, and calculates the target concentration and removal rate using the cellular automata-Markov chain Monte Carlo method. Thus, risk assessment of water bodies can be achieved. The results show that: (1) the concentration of the target substance in each process stage has obviously decreased during the life cycle, with an average concentration of 3–18 mg/L; (2) in the life cycle, the highest removal rate of target concentration in each process section can reach 85%; (3) the concentration of target substances SS, COD, TN, TN, TP, and TP at the outlet of the sewage treatment plant is relatively high. Practice has proven that this research method can assess the risk factors of receiving water bodies, so as to improve the scientific, refined and standardized environmental management.

Keywords: receiving water body; life cycle; risk factors; CA-MCMC method; traceability analysis

1 Introduction

With the improvement of living standards, people pay more and more attention to environmental problems, especially the pollution of water resources, which is one of the main environmental problems in China [1]. With the process of industrialization and the development of urbanization, a lot of water pollution has occurred in industrial production, urban drainage, agriculture and forestry irrigation, animal husbandry, and other processes, having a serious impact on water quality. Therefore, timely monitoring, treatment, and control of the source of pollution, as well as timely remedial action by relevant management staff, are required to reduce the scope of water pollution [2].

The life cycle assessment (LCA) method is a systematic evaluation of the impact of products, services, and processes on the environment in the whole life cycle, which mainly includes four steps: definition of objectives and scope, life cycle invention, impact assessment, and result interpretation. The LCA method is widely applied in manufacturing, construction, industry, and other fields, and this article can be used to evaluate the environmental impact of transportation, energy consumption, and sewage treatment at different stages, and this article provides guidance for environmental protection design, production, and consumption.

Relevant researchers use the LCA method to study and analyze water pollution. Wang et al. [4] used the LCA method to evaluate the sewage discharge problem, comparing the impact of sewage discharge standards on the environment, optimizing the sewage discharge scheme, and reducing the negative impact of water pollution. However, this method needs to collect a lot of data and information and make complex calculations to get the optimization results. Gallego-Schmid et al. [5] studied the micro-pollutants (antibiotics, phenolic compounds, nonionic surfactants, heavy metals) in the receiving water, commented on the effects of different treatment methods on different influencing factors, and then selected the optimal treatment process. Due to the differences in environmental standards in different regions, the application scope of this method is limited. Abyar et al. [6] built a comprehensive impact assessment model of carbon footprint, environment, and economy in the whole life cycle, comprehensively evaluated energy consumption, material consumption, and pollution discharge, and analyzed the comprehensive impact results. The comparability of the evaluation results of this method needs further verification. Lyu et al. [7] used the LCA method to reveal the life cycle environmental influence of the two-stage wastewater treatment system in CIP and improved the treatment capacity of high pollution load in the factory. This method adopted a two-stage wastewater treatment system, which easily produces data redundancy. Zhou et al. [8] used the LCA method to optimize the endogenous pollution of natural water caused by sediments and reduced the secondary environmental impact during the treatment and disposal of dredged sludge. This method does not trace the source of sediments, which affects the durability of the evaluation results.

Based on the previous research results, this article applies the LCA method to establish an evaluation system for the receiving water body. Traceability analysis is conducted on the risk factors of the receiving water body. A self-developed evaluation method is used to construct a characterization model for environmental objectives and scope definition, reducing computational complexity. Furthermore, the water quality model is coupled with the LCA method to calculate the target object’s concentration throughout the life cycle, avoiding data redundancy. The cellular automata-Markov chain Monte Carlo (CA-MCMC) method is employed to calculate the removal rates of suspended solids (SS), chemical oxygen demand (COD), total nitrogen (TN), and total phosphorus (TP) in various stages of the treatment process, such as coarse and fine grids, primary sedimentation tank, A/O process, secondary sedimentation tank, sewage pumping station, and disinfection tank. Based on these calculations, the impact assessment results are obtained. The joint analysis method is used to explain the results and complete the traceability of risk factors. The experimental results show that this method can obtain the target concentration and removal rate values in different sampling points in a short time, locate the sampling points with higher numerical results of risk factors, improve the durability and comparability of the research method, and broaden the application scope.

2 Methods

2.1 Research objects and sampling

A sewage treatment plant in Nanjing and its receiving water body are selected as the research object. The sewage treatment plant covers an area of 9.0209 ha, mainly intercepting and centrally treating industrial and domestic sewage, and the treated sewage is discharged into the lower reaches of Qinhuai River. The designed treatment scale is 350,000 t/d, and the sewage is treated by an anaerobic-anoxic-aerobic biological nitrogen and phosphorus removal (A²/O) process, and the sludge is dewatered in the dewatering room to form mud cakes for transportation. The specific process flow is shown in Figure 1.

Figure 1

Schematic diagram of process flow of sewage treatment plant.

There are five water sampling points in the receiving river, which are divided into grid forward water, primary sedimentation tank water, A²/O process water, secondary sedimentation tank water, and disinfection tank water. The specific acquisition point location is shown in Figure 2.

Figure 2

Receiving water collection point.

2.2 Research method

2.2.1 Construct a characterization model of environmental objectives and scope definition

Defining environmental objectives and scope enables effective data comparison of functional units, thereby reducing the computational complexity of the entire LCA [9,10,11]. The environmental catalogue of receiving water body is constructed by the LCA method, which includes SS, COD, TN, and TP targets. SS usually refers to suspended particulate matter in water, and SS can be used as an important index to evaluate the water quality and pollution degree of the receiving water body. When the SS concentration in the receiving water is too high, it may pose a potential threat to aquatic organisms and human health. COD refers to COD, which is an index to measure the content of organic substances in water. A high concentration of COD usually means that the water is polluted by organic substances, which may come from different sources such as industrial wastewater, agricultural discharge, and urban sewage. TN refers to total nitrogen, which is an index to evaluate the nitrogen content in water, including inorganic nitrogen and organic nitrogen. A high concentration of TN usually means that water is polluted by nitrogen sources. TP refers to total phosphorus, which is an index to evaluate the phosphorus content in water. A high concentration of TP usually means that the water is polluted by phosphorus sources.

The target factors of SS, COD, TN, and TP were calculated, and their evaluation data were obtained. Using a self-built quantification method, the characterization model I _i of environmental objectives and scope definition is constructed as follows. The range of environmental objectives is

(1) I i = EP i × EC i ,

where EP_i is the EP correlation coefficient of target i and EC_i is the emission of target i per functional unit. Bring SS, COD, TN, and TP targets into the characterization model to obtain specific evaluation data. The target scope of ISS, ICOD, ITN, and ITP is

(2) I SS = EP SS × EC SS I COD = EP COD × EC COD I TN = EP TN × EC TN I TP = EP TP × EC TP ,

where EP_SS, EP_COD, EP_TN, and EP_TP are EP correlation coefficients of SS, COD, TN, and TP; and EC_SS, EC_COD, EC_TN, and EC_TP are the emissions of SS, COD, TN, and TP per functional unit.

2.2.2 Invention of coupling water quality model to obtain life cycle

In order to effectively quantify the impact of SS, COD, TN, and TP targets on the receiving water body, the target characterization parameters are coupled with the water quality model. The amount of pollutants treated throughout the entire cycle of a sewage treatment plant [12] was calculated.

The steady-state assumption in water quality models refers to the assumption that the water quality state of the system remains constant within the research time range, i.e. there is no significant change. According to the steady-state assumption, various water quality parameters in the system (such as dissolved oxygen concentration, pollutant concentration, etc.) maintain stable distribution in space and time. Based on the water quality model, a new water quality model is established by using the steady-state assumption in the model, and the expression is

(3) G i = M n + I i m n − 1 ,

where M _n is the pollutant discharge part of this area, m _n−1 is the discharge part of the sewage treatment plant, and G i is the water quality models.

The targets of SS, COD, TN, and TP are entered into the new water quality model to obtain specific quantitative data. The characteristic calculation formula of G _SS, G _COD, G _TN, and G _TP is

(4) G SS = M n + I SS m n − 1 G COD = M n + I COD m n − 1 G TN = M n + I TN m n − 1 G TP = M n + I TP m n − 1 .

Assuming that the target concentration in the water quality model changes in the longitudinal direction (velocity direction X), material mixing occurs on the cross-section of the water body (horizontal direction Y and vertical direction Z), and the target concentration in the receiving water body is expressed as follows:

(5) f i = ∂ λ i ∂ t h i v G i ,

where f _i is the concentration of target i in the receiving water, λ _i is the longitudinal diffusion coefficient of the target i in the receiving water body, h is the self-purification coefficient of the receiving water body, and v is the flow rate of the receiving water body.

By solving equation (5), the target concentrations of SS, COD, TN, and TP can be obtained as follows:

(6) f SS = ∂ λ SS ∂ t h v G SS f COD = ∂ λ COD ∂ t h v G COD f TN = ∂ λ TN ∂ t h v G TN f TP = ∂ λ TP ∂ t h v G TP ,

where f _SS, f _COD, f _TN, and f _TP are the concentrations of SS, COD, TN, and TP in the receiving water; and λ _SS, λ _COD, λ _TN, and λ _TP are the vertical diffusion coefficients of SS, COD, TN, and TP in the receiving water.

Equations (5) and (6) are established based on a water quality model. These equations describe the changes in target substance concentration in the vertical direction and the mixing process of the substance in the cross-section of the water body.

Equation (5) represents the change in target substance concentration in the receiving water body, which includes the effects of factors such as longitudinal diffusion, self-purification, and flow rate.

Equation (6) is the result obtained by solving equation (5), which represents the concentration of target substances (such as solid SS, COD, TN, and TP) in the receiving water body calculated in the model.

The physical meaning of these equations is to describe the transport and mixing process of target substances in water bodies. Equation (5) considers these factors and describes the changes in the concentration of the target substance. Equation (6) converts the solution result of equation (5) into the actual substance concentration value, providing information on the concentration of the target substance in the receiving water body.

Quantize f _i, and the expression is

(7) f i ′ = η u i t ,

where η is the oxygen consumption of the target i in the receiving water body at position x, u _i is the mass of the target i passing through the interface within a fixed time t, and t is the diffusion time of the target i.

2.2.3 Impact assessment of receiving water targets based on CA-MCMC

The cellular automata (CA) model is a dynamic model [13]. The update of the cellular state will change the state of the whole system, and the target of the receiving water body can be traced by the spontaneous evolution process. However, the number of cells in the CA model is limited, and the quantified target data have a certain discreteness. It is necessary to combine the Markov-chain Monte Carlo (MCMC) method to make the cell state the life cycle state of the target, calculate the removal rate of SS, COD, TN, and TP targets in the whole life cycle of the sewage treatment plant process, and complete the impact assessment of the target in the receiving water body.

The Markov Chain Monte Carlo method (MCMC method) is a sampling method [14], In this method, the next state of the system depends on the current state and has Markov properties. The CA model combines the two-dimensional mathematical model in the MCMC algorithm [15] and inputs data such as target type, target concentration, receiving water flow rate, diffusion time, and so on into the CA model. The MCMC algorithm was used to calculate the removal rate of target concentration, which is expressed as follows:

(8) p i = α f i − in ′ - β f i − out ′ Q f i − in ′ × 100 % ,

where f i − in ′ is the influent concentration of target i, f i − out ′ is the effluent concentration of target i, Q is the water flow of the receiving water body, α is the input rate of the target i, and β is the degradation rate of target i in the receiving water.

2.2.4 Pollutant analysis based on joint analysis method

The joint analysis method is used to explain the evaluation results of the impact of the target object in the receiving water body, to complete the traceability of risk factors, and to locate the geographical location with high solubility of the target object [16]. The joint analysis method calculates the risk factor of the target object, which is expressed as follows:

(9) ζ = ∏ i = 1 n l i t W ( b i − a i ) p i ,

where n is the total emission concentration of the target, l _i is a virtual variable composed of the attributes of the target object i, W is the utility value correlation constant, a _i is the upper limit of the source term, and b _i is the lower limit of the source term. The target risk factor ζ is the traceability index of the receiving water body, and the numerical result is usually between 0 and 1. The greater ζ indicates that the water quality of the receiving water body in the geographical location is low, and the water body is eutrophic at this time. According to the zeta value, the source of the target in the life cycle of the receiving water body is completed.

3 Results

The LCA system and traceability of risk factors in the receiving water body help environmental management identify pollution sources, calculate target concentrations and removal rates, and develop strategies for managing and monitoring activities to protect water body health and reduce environmental pollution. The full life cycle refers to the process of changes in target substances throughout the entire life cycle of a sewage treatment plant. In sewage treatment plants, different processes can have an impact on the concentration of target substances. Therefore, by analyzing the trend of changes in target substances in each process, one can understand their changes throughout the entire life cycle.

Assessing the trend of changes in target substances throughout the entire lifecycle can be done by collecting concentration data of target substances in various processes, analyzing and comparing them to understand their changing trends in different processes. Based on the characteristics and environmental quality of the target substance, the source of pollutants were identified and their risk factors were determined. Based on the evaluation results, potential risk factors were identified and corresponding measures were taken to reduce the potential impact of the target substance on the water environment.

3.1 Analysis of target concentration in each process section in life cycle

By analyzing the concentration of the target substance in each process section of the sewage treatment plant, we can understand the changing trend of the target substance in different treatment processes, optimize the sewage treatment process in a targeted manner, and provide data reference for further water environmental protection. The specific results are shown in Figure 3.

Figure 3

Results of target concentration at each sampling point of the sewage treatment plant.

As shown in Figure 3, the concentrations of SS, COD, TN, and TP of the target substance have decreased after being treated by the sewage treatment plant. The concentration of SS, COD, TN, TN, TP, and TP after effluent from the disinfection pool is 9.6, 23.1, 18.2, 21.5, 16.4, 19.8, and 2.7 mg/L, respectively. This is because the process of sewage treatment plants can effectively remove organic pollutants, precipitated pollutants, heavy metal pollutants, and so on in the receiving water. The concentration of pollutants in the treated wastewater is reduced.

3.2 Analysis of target concentration removal rate in each process section in life cycle

The sampling point are set as shown in the following Figure 4.

Figure 4

Sampling point setting.

The project area is a coexistence of the old urban area, the new urban area, and the urban–rural fringe. The drainage network constructed in the early stages of the old urban area adopts a confluence system, and the rainwater and sewage pipeline system has been buried in the new urban area along with the road construction according to the requirements of the diversion system. The total area of the area is 19.5 km²; there are 32.8 km of newly built diversion sewage pipelines and 17.3 km of combined drainage pipelines to be repaired. The average annual COD concentration of the sewage treatment plant in the area is less than 100 mg/L, and the average COD concentration on sunny days is only 100–120 mg/L, which is much lower than the design inflow concentration of around 200 mg/L.

Sampling is a key step in obtaining water samples in water quality monitoring and research. Before sampling, it is necessary to prepare sampling equipment and select appropriate sampling points. During the sampling process, the sampling containers and instruments should be cleaned first, and appropriate sampling methods should be selected, such as surface water, deep water, rivers, lakes, or groundwater. The appropriate sampling quantity and frequency should be determined, sampling information should be recorded, and the samples should be labelled. After sampling, tightly seal the sample container and send it to the laboratory for analysis as soon as possible. Following accurate sampling methods, standard guidelines, and quality control measures can ensure reliable water sample data is obtained.The sampling time is June 2023. Five samples were collected for every 10 days.

When determining conventional water quality parameters, standard methods such as colorimetry can be used for the analysis of COD. First, an appropriate amount of sample was taken from the collected water sample and it was filtered with filter paper to remove SS. Then, the filtered sample was transferred to a pre calibrated container. Next, an appropriate amount of highly oxidizing chemicals (such as potassium sulfate potassium chromate solution) was added to a set of parallel samples to oxidize the oxidizable substances in the sample. After reacting with the sample and reagent for a period of time, the color of the solution changes was observed. Next, a spectrophotometer or colorimetric meter was used to measure the absorbance of the solution at a specific wavelength. Blank reagents were used for parallel processing, and the same measurements were performed to eliminate the influence of other factors in the control group. By comparing with standard curves or calculation formulas, the content of COD in the sample can be calculated.

The detailed data of SS, COD, TN, and TP used in this study are shown in Table 1.

Table 1

Data List (mg/L)

Number	SS	COD	TN	TP
1	345	390	388	325
2	38	477	428	411
3	501	486	117	605
4	502	224	351	421
5	257	537	567	224

By analyzing the removal rate of target concentration in each process section of the sewage treatment plant, we can understand the removal effect of different treatment processes and provide a reference for the optimization and improvement of the target treatment process in receiving water. The specific results are shown in Figure 5.

Figure 5

Removal results of target concentration at each sampling point of the sewage treatment plant.

It can be seen from Figure 5 that the target concentration removal rate of the receiving water body at sampling point 3 is high, and the TP concentration removal rate is the highest, which is 85%. This is because the receiving water in sampling point 3 has been treated by the A²/O process, and the target concentrations of SS, COD, TN, and TP are simultaneously removed through the aerobic zone, anoxic zone, and anaerobic zone. At the same time, the A²/O process adopts advanced technologies such as denitrification and nitrogen and phosphorus removal, which can realize the efficient removal of TN and TP.

3.3 Traceability analysis of target in the life cycle of receiving water body

There are industrial production drainage points (118°57′E, 31°23′N), urban domestic sewage drainage points (118°57′E, 31°37′N), agricultural and forestry irrigation drainage points (119°01′E, 31°41′N), and animal husbandry drainage points (31°41′N). The risk factors for each drainage point ζ were calculated. A higher ζ value indicates poorer water quality at the discharge point and a higher degree of eutrophication in the water body. It is necessary to strengthen the sewage treatment degree and control the pollution of the target. The specific results are shown in Figure 6.

Figure 6

Results of target risk factors at different drainage points.

It can be seen from Figure 6 that with the extension of diffusion time, the numerical results of target risk factors of industrial production drainage points, urban domestic sewage drainage points, agricultural and forestry irrigation drainage points, and animal husbandry drainage points show an upward trend. Among them, the risk factors of agricultural and forestry irrigation and animal husbandry are all below 0.5, the risk factors of urban domestic sewage are 0.8, and the risk factors of industrial production are 0.9. According to the magnitude of the risk factors of the target, the target of industrial production has the greatest risk to the receiving water environment, followed by urban domestic sewage, while agricultural and forestry irrigation and animal husbandry have little impact on the receiving water environment. Therefore, for water environmental protection, environmental management departments should focus on the control of industrial enterprises and urban domestic sewage discharge and, at the same time, strengthen the environmental management of agriculture and animal husbandry.

Based on the above results and analysis, it can be concluded that the process of sewage treatment plants can effectively remove organic pollutants, sediment pollutants, and heavy metal pollutants from the receiving water, thereby reducing the concentration of target substances in the treated wastewater. In each treatment section of the sewage treatment plant, the removal effect of sampling point 3 is good, especially for the highest removal rate of TP concentration, which reaches 85%. This is because advanced technology is used to achieve efficient nitrogen and phosphorus removal. Through traceability analysis, it was found that industrial production drainage points and urban domestic sewage discharge points have the greatest impact on the target risk factors of the receiving water environment, while agricultural and forestry irrigation and livestock discharge have a relatively small impact on the environment. Therefore, in terms of water environment protection, it is necessary to strengthen the control of industrial and urban domestic sewage discharge and strengthen environmental management in agriculture and animal husbandry. In summary, based on the full LCA system and risk factor traceability research, optimizing sewage treatment processes, improving the removal effect of target substances, and strengthening the management and control of target pollutant discharge points will provide data reference and guidance for further water environment protection.

4 Conclusion

This article investigates the traceability method of target risk factors in the life cycle of a receiving water body. A self-developed quantitative characterization model is used to define environmental objectives and scope. Coupled with a water quality model, the concentration of the target substance is calculated, providing insights into the life cycle intervention. The CA-MCMC method is employed to calculate the removal rates of various pollutants in different stages of the sewage treatment process. Based on the analysis, the impact assessment results indicate that industrial production and urban domestic sewage upstream of the sewage treatment plant pose significant environmental risks to the receiving water body.

To ensure water health protection, environmental management departments should focus on strengthening the supervision of industrial enterprises and urban domestic sewage. Optimizing the processes within sewage treatment plants will help reduce the environmental impact of target substances, ultimately promoting sustainable environmental development.

Funding information: The research was supported by the Taihu Lake Water Pollution Control provincial special Fund Project “Risk Assessment of Toxic and Harmful Pollutants in Ecological Protection Leading Area” (TH2018404).
Author contributions: Xiaoming Ren identified this problem and designed the method. Yang Qiu performed the model building and writing the manuscript. Zixuan Wang and Yukun Zhou performed the experiments. All authors read and approved the final manuscript.
Conflict of interest: Authors state no conflict of interest.
Data availability statement: All relevant data are included in the paper.

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Received: 2023-08-16

Revised: 2023-10-24

Accepted: 2023-11-14

Published Online: 2023-12-15

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

Articles in the same Issue

https://doi.org/10.1515/geo-2022-0580

Keywords for this article

receiving water body; life cycle; risk factors; CA-MCMC method; traceability analysis

Creative Commons

BY 4.0

Number	SS	COD	TN	TP
1	345	390	388	325
2	38	477	428	411
3	501	486	117	605
4	502	224	351	421
5	257	537	567	224

Number	SS	COD	TN	TP
1	345	390	388	325
2	38	477	428	411
3	501	486	117	605
4	502	224	351	421
5	257	537	567	224

Number	SS	COD	TN	TP
1	345	390	388	325
2	38	477	428	411
3	501	486	117	605
4	502	224	351	421
5	257	537	567	224