Drinking water disinfection by-product generation prediction method based on reaction kinetic model

Abstract

The invention discloses a drinking water disinfection by-product generation prediction method based on a reaction kinetic model, and belongs to the technical field of drinking water treatment and drinking water quality prediction, and the method is realized based on the following steps: 1) constructing a disinfection by-product generation kinetic model of a model compound and determining the reaction rate of each step; 2) constructing and optimizing a disinfection by-product generation kinetic model of the natural organic matter on the basis of the obtained reaction rate to obtain a disinfection by-product generation kinetic model of an actual water body; 3) establishing a prediction method for the concentration of each component in the model; and 4) inputting the measured concentration of each component in the actual water body into the constructed model, and calculating and predicting a disinfection by-product generation kinetic result of the actual water body through the model. The method fully considers the generation kinetics of the disinfection by-products of the actual water body under different space (time) distribution, can quickly predict the generation of various disinfection by-products which are managed and controlled and are not managed and controlled but have high toxicity, provides early warning for the effluent quality of drinking water treatment, and ensures the safety of drinking water.

Description

(I)TECHNICAL FIELD

[0001] The present application relates to a drinking water disinfection by-product generation prediction method based on a reaction kinetics model, and belongs to the technical field of drinking water treatment and drinking water quality prediction. (II)BACKGROUND

[0002] The disinfection of drinking water to control the spread of related diseases is a major achievement in the field of public health, but disinfectants such as chlorine can react with dissolved organic matter in the water source to generate halogenated disinfection by-products that are toxic. At present, more than 800 types of disinfection by-products have been detected in drinking water, and many countries have also controlled the concentration of common disinfection by-products (such as trihalomethane and haloacetic acid) in drinking water to reduce public exposure risk. However, emerging disinfection by-products such as halogenated acetaldehyde, halogenated acetonitrile and halogenated acetamide have not yet been controlled, although their concentrations are relatively low, but their toxicity is higher than that of trihalomethane and haloacetic acid. In addition, the concentration of bromide ions in drinking water sources ranges from less than 10 micrograms per liter to 1000 micrograms per liter, and human activities such as seawater intrusion, industrial wastewater discharge, and mixing of desalinated seawater and surface water can increase the concentration of bromide ions in drinking water sources. When bromide-containing source water is chlorinated, brominated disinfection by-products are produced, which have cell toxicity and genetic toxicity that are tens to hundreds of times higher than that of chlorinated analogues. The above disinfection by-products can all be key factors that cause cell toxicity of drinking water, thereby threatening drinking water safety.

[0003] Given the different toxicological significance of different disinfection by-products, the length of chlorine exposure (i.e. the spatial distribution of water points) and the content of specific halogen components (such as bromide ions) are key factors in the water supply system, which can significantly affect the generation of disinfection by-products and health risk assessment. Recent studies have shown that extending the chlorine exposure time (1-7 days) can increase the concentration of four types of trihalomethane and five types of haloacetic acid by 62%-76%. However, paradoxically, extending the chlorine exposure time reduces the total cell toxicity by 40%-47%, which can lead to an underestimation of the health risks associated with disinfection by-products in the water supply network near the treatment facility. Although there have been many studies on predicting the kinetics of disinfection by-products, most models focus on trihalomethane and haloacetic acid, and there are few models for other or all halogenated disinfection by-products. Moreover, most existing models focus on the correlation between "disinfection by-product concentration" and "water quality parameters or disinfection conditions", and there are few models based on reaction kinetics. (III)SUMMARY

[0004] In view of the shortcomings of existing models, the purpose of the present application is to construct a kinetic model that introduces multiple factors, so that it is more suitable for the actual treatment and distribution process of drinking water, and is used to quickly predict the generation of various disinfection by-products, providing a reference for the early control of disinfection by-products.

[0005] To achieve the above object, the present application adopts the following technical solutions:

[0006] (1) Selecting different kinds of model compounds to represent the precursors of disinfection by-products in actual water bodies;

[0007] Further, the model compounds phenol and m-diphenol are selected as representatives of phenolic substances in actual water bodies, the model compound citric acid is selected as a representative of carboxyl-containing substances in actual water bodies, and the model compounds aspartic acid, histidine, tryptophan and tyrosine are selected as representatives of amino acid (organic nitrogen) substances in actual water bodies.

[0008] (2) Disinfection by-product generation kinetics experiment of model compounds;

[0009] Further, the disinfection by-product generation kinetics experiment of the model compounds includes preparation of disinfectants and reaction of the model compounds with the disinfectants.

[0010] Among them, the disinfectant hypochlorous acid is obtained by diluting sodium hypochlorite stock solution, and the disinfectant hypobromous acid is obtained by reacting hypochlorous acid with potassium bromide.

[0011] Among them, the model compounds and disinfectants need to be kept in excess of the disinfectant conditions for reaction, and after the reaction meets the specified time, ascorbic acid needs to be used to quench the residual disinfectant in the reaction system.

[0012] (3) Constructing a disinfection by-product generation kinetics model of model compounds;

[0013] Further, the disinfection by-product generation kinetics model of the model compounds includes a reaction model of the model compounds with disinfectants and a degradation model of disinfection by-products.

[0014] Among them, the reaction model of the model compounds with disinfectants is as follows:

[0015] MC + HOX→ Pre (1)

[0016] Pre + HOX→DBPs (2)

[0017] MC + HOX→ Pro (3)

[0018] In the formula, MC represents the seven kinds of model compounds described in step (1); HOX represents two disinfectants, hypochlorous acid and hypobromous acid, which represent the generation processes of chlorinated disinfection by-products and brominated disinfection by-products when bromide ions are present; Pre represents the precursors of disinfection by-products generated by the reaction of model compounds with disinfectants; Pro represents other non-disinfection by-product products generated by the reaction of model compounds with disinfection by-products, and the generation reactions of these products and the generation reactions of disinfection by-products are mutual competitive reactions.

[0019] the degradation model of the disinfection by-products includes an alkaline catalysis hydrolysis model of the disinfection by-products and a reaction model of the disinfection by-products and residual disinfectant;

[0020] The alkaline catalysis hydrolysis model of the disinfection by-products is shown as follows:

[0021] DBPs→DBPs, hy (4)

[0022] In the formula, DBPs, hy represents the hydrolysis product of the disinfection by-products

[0023] The reaction model of the disinfection by-products and residual disinfectant is shown as follows:

[0024] DBPs + HOX→DBPs, pro (5)

[0025] In the formula, DBPs, pro represents the oxidation product of the disinfection by-products.

[0026] (4) determining the rate of each step in the model compound disinfection by-products generation kinetics model;

[0027] Further, k H2O represents the rate of alkaline catalysis hydrolysis of the disinfection by-products, k HOX represents the reaction rate of the disinfection by-products and residual disinfectant; k1 represents the rate of reaction of the model compound and the disinfectant to generate the disinfection by-products precursor, k2 represents the rate of reaction of the disinfection by-products precursor and the disinfectant to generate the disinfection by-products, k3 represents the rate of reaction of the model compound and the disinfectant to generate other products of the disinfection by-products, k1, k2, k3 are obtained by fitting the actual concentration data of the disinfection by-products from the model compound kinetics experiment described in step (2) according to the disinfection by-products generation kinetics model described in step (3).

[0028] (5) disinfection by-products generation kinetics experiment of natural organic matter;

[0029] Further, the kinetics experiment includes direct chlorination experiment of natural organic matter water and chlorination experiment of natural organic matter water containing bromide ions.

[0030] In the formula, DBPs, hy represents the hydrolysis product of the disinfection by-products

[0031] The chlorination experiment of natural organic matter water containing bromide ions is a chlorination experiment in which a certain amount of potassium bromide is first added to the natural organic matter water, and then hypochlorous acid is added.

[0032] (6) a disinfection by-product generation kinetics model of natural organic matter is constructed;

[0033] Further, the disinfection by-product generation kinetics model of natural organic matter includes a hypobromous acid generation kinetics model, a phenolic substance disinfection by-product production kinetics model, a carboxyl-containing substance disinfection by-product kinetics model, an amino acid (organic nitrogen) substance disinfection by-product kinetics model, a kinetics model of reaction of non-disinfection by-product precursors with disinfectants, and a disinfection by-product degradation model.

[0034] The hypobromous acid generation kinetics model is as follows:

[0035] Br - + HOCl→HOBr + Cl - (6)

[0036] The phenolic substance disinfection by-product production kinetics model is as follows:

[0037] NOM phenolic + HOCl→Pre (7)

[0038] Pre + HOCl→Cl-DBPs (8)

[0039] NOM phenolic + HOCl→Pro (9)

[0040] NOM phenolic + HOBr→Pre (10)

[0041] Pre + HOBr→Br-DBPs (11)

[0042] NOM phenolic + HOBr→Pro (12)

[0043] In the formula, NOM phenolic represents phenolic substances in natural organic matter; Cl-DBPs are chlorinated disinfection by-products; and Br-DBPs are brominated disinfection by-products.

[0044] The carboxyl-containing substance disinfection by-product kinetics model is as follows:

[0045] NOM carboxyl + HOCl→Pre (13)

[0046] Pre + HOCl→Cl-DBPs (14)

[0047] NOM carboxyl + HOCl→Pro (15)

[0048] NOM carboxyl + HOBr→ Pre (16)

[0049] Pre + HOBr→ Br-DBPs (17)

[0050] NOM carboxyl + HOBr→ Pro (18)

[0051] where NOM carboxyl represents the carboxylic acid-containing substances in NOM;

[0052] The kinetics model of disinfection by-products for amino acid (organic nitrogen) -containing substances in NOM is shown as follows:

[0053] NOM AAs + HOCl→ Pre (19)

[0054] Pre + HOCl→ Cl-DBPs (20)

[0055] NOM AAs + HOCl→ Pro (21)

[0056] NOM AAs + HOBr→ Pre (22)

[0057] Pre + HOBr→ Br-DBPs (23)

[0058] NOM AAs + HOBr→ Pro (24)

[0059] where NOM AAs represents the amino acid (organic nitrogen) -containing substances in NOM;

[0060] The kinetics model of reaction of non-disinfection by-product precursors with disinfectants is shown as follows:

[0061] NOM dec + HOCl→ Pro (25)

[0062] NOM dec + HOBr→ Pro (26)

[0063] where NOM dec represents the non-disinfection by-product precursors in NOM that react with disinfectants but do not generate disinfection by-products, and the reaction of these substances with disinfectants and the generation of other disinfection by-products are competitive reactions;

[0064] The degradation model of disinfection by-products is shown as follows:

[0065] Cl-DBPs→DBPs, hy (27)

[0066] Br-DBPs→DBPs, hy (28)

[0067] Cl-DBPs + HOCl→DBPs, pro (29)

[0068] Cl-DBPs + HOBr→DBPs, pro (30)

[0069] Br-DBPs + HOCl→DBPs, pro (31)

[0070] Br-DBPs + HOBr→DBPs, pro (32)

[0071] In the formula, DBPs, pro represents the product generated by the reaction of disinfection by-products with disinfectants.

[0072] (7) Determine the rate of each step in the natural organic matter disinfection by-product generation kinetics model;

[0073] Further, k6 represents the reaction rate of bromide ion with hypochlorous acid to generate hypobromous acid; k7, k 10 represent the rate of reaction of phenolic substances in natural organic matter with disinfectants to generate disinfection by-product precursors, k9, k 12 represent the rate of reaction of phenolic substances in natural organic matter with disinfectants to generate other products that are not disinfection by-products; k 13 , k 16 represent the rate of reaction of carboxyl-containing substances in natural organic matter with disinfectants to generate disinfection by-product precursors, k 15 , k 18 represent the rate of reaction of carboxyl-containing substances in natural organic matter with disinfectants to generate other products that are not disinfection by-products; k 19 , k 22 represent the rate of reaction of amino acid (organic nitrogen) substances in natural organic matter with disinfectants to generate disinfection by-product precursors, k 21 , k 24 represent the rate of reaction of amino acid (organic nitrogen) substances in natural organic matter with disinfectants to generate other products that are not disinfection by-products; k7-k 24 are obtained by fitting the actual disinfection by-product concentration data obtained from the natural organic matter disinfection by-product generation kinetics experiment described in step (5) to the disinfection by-product generation kinetics model described in step (6), and the fitting process is based on the rate range of the corresponding model compounds obtained in step (4).

[0074] (8) Establish a method for predicting the concentration of each component in the kinetics model

[0075] Further, the linear relationship between phenol concentration and absorbance at 254 nm ultraviolet wavelength is established, and the result measured by natural organic matter is corrected to calculate the concentration of phenol in the actual water body; the linear relationship between the concentration of dissolved organic nitrogen in the actual water body and the consumption of disinfectant in the disinfection process (20 minutes) is established, and the concentration of amino acid (organic nitrogen) is calculated according to the proportion of amino acid in organic nitrogen; the concentration of carboxyl substance is predicted according to the proportion of carboxyl substance in dissolved organic carbon.

[0076] (9) Disinfection by-product generation kinetics model of the actual water body

[0077] Further, the concentration of each component required for the kinetic model of the actual water body obtained in step (7) is measured

[0078] The model compounds of the present application, phenol, m-diphenol, citric acid, aspartic acid, histidine, tryptophan, tyrosine and disinfectant sodium hypochlorite are commercially available products.

[0079] The disinfection by-products in the present application are quantitatively detected by commercially available high-efficiency gas chromatography-electronic detector.

[0080] In the present application, Kintecus software is used to complete the modeling of the kinetic model, and then the prediction data is calculated by model fitting in the Kintecus software.

[0081] Compared with the existing disinfection by-product kinetics model, the present application constructs a kinetics model introducing multiple factors, fully considers the disinfection by-product generation kinetics of different components in the actual water body under different spatial (time) distribution conditions, can quickly predict the generation of multiple disinfection by-products under different spatial distribution, and can give corresponding early warning of the quality of treated drinking water through analysis and prediction results, which is more suitable for the actual treatment and distribution process of drinking water. (IV) DESCRIPTION OF DRAWINGS

[0082] Figure 1 It is the flow chart of the application of the method of the present application.

[0083] Figure 2 It is the linear relationship diagram between phenol concentration and absorbance at 254 nm ultraviolet wavelength in the method of the present application.

[0084] Figure 3 It is the linear relationship diagram between the concentration of dissolved organic nitrogen and the chlorine consumption of the disinfection water body in 20 minutes in the method of the present application.

[0085] Figure 4 It is the disinfection by-product generation kinetics result diagram of high bromine water body 1 in an embodiment of the method of the present application.

[0086] Figure 5 Figure 2 shows the disinfection by-product formation kinetics results for low bromide water bodies 2 and 3 in an embodiment of the method of the present application. (V) DETAILED DESCRIPTION

[0087] The present application will now be described in more detail with reference to the following embodiments. Other advantages and features of the application will be apparent from this description. The application is not limited to the following examples, and the contents of the present specification can be modified and changed in various ways without departing from the technical idea of the present application.

[0088] Reference Figure 1 Figure 1 shows a method for rapid prediction of disinfection by-product concentration in drinking water based on a kinetic model, the method comprising the following steps:

[0089] Step 1: Perform disinfection by-product formation kinetics experiments for 7 model compounds, construct a disinfection by-product formation kinetics model for the model compounds using Kintecus software and determine the reaction rate of each step, the reaction rate of each step corresponding to the five types of disinfection by-product formation kinetics models of different model compounds is shown in Table 1, Table 2, Table 3, Table 4 and Table 5, respectively.

[0090] Table 1 Reaction rate constants of each step in the trihalomethane formation kinetics model

[0091]

[0092] Table 2 Reaction rate constants of each step in the haloacetic acid formation kinetics model

[0093]

[0094]

[0095] Table 3 Reaction rate constants of each step in the haloacetaldehyde formation kinetics model

[0096]

[0097]

[0098] Table 4 Reaction rate constants of each step in the haloacetonitrile formation kinetics model

[0099]

[0100] Table 5 Reaction rate constants of each step in the haloacetamide formation kinetics model

[0101]

[0102] Step 2: Perform disinfection by-product formation kinetics experiment of natural organic matter, use Kintecus software to construct disinfection by-product formation kinetics model of natural organic matter water body, reaction rate of each step in different components is fitted according to rate in disinfection by-product formation kinetics model of corresponding model compound, finally obtain reaction rate of each step in disinfection by-product formation kinetics model of actual water body. Corresponding step rate results in five kinds of disinfection by-product formation kinetics models are shown in Table 6, Table 7, Table 8, Table 9 and Table 10 respectively;

[0103] Table 6 Disinfection by-product formation kinetics model of trichloromethane and tribromomethane in actual water body chlorination process and reaction rate constant of each step

[0104]

[0105] Table 7 Disinfection by-product formation kinetics model of dichloroacetic acid and dibromoacetic acid in actual water body chlorination process and reaction rate constant of each step

[0106]

[0107] Table 8 Disinfection by-product formation kinetics model of trichloroacetic acid and tribromoacetic acid in actual water body chlorination process and reaction rate constant of each step

[0108]

[0109] Table 9 Disinfection by-product formation kinetics model of trichloroacetaldehyde and tribromoacetaldehyde in actual water body chlorination process and reaction rate constant of each step

[0110]

[0111] Table 10 Disinfection by-product formation kinetics model of dichloroacetonitrile and dibromoacetonitrile in actual water body chlorination process and reaction rate constant of each step

[0112]

[0113] Step 3: Establish linear relationship between phenol concentration and absorbance at 254 nm ultraviolet wavelength, results are shown in Figure 2 , and the results of natural organic matter determination are corrected to calculate the predicted value of the concentration of phenolic substances in dissolved organic matter in actual water body, as follows:

[0114] C phenolic = 3.3×10 -5 ×UV 254 (33)

[0115] In the formula, C phenolic is the concentration of phenolic substances (mol / L), UV 254Absorbance of the actual water body at 254 nm UV wavelength;

[0116] A linear relationship between the concentration of dissolved organic nitrogen in the actual water body and the consumption of disinfectant during the disinfection process (20 minutes) is established, and the prediction of the concentration of amino acid (organic nitrogen) substances in the actual water body is corrected according to the proportion of amino acid substances in organic nitrogen, as follows:

[0117] C AAs = 2.89 x 10 -7 C chlorine (34)

[0118] In the formula, C AAs represents the concentration of amino acid (organic nitrogen) substances in the actual water body (mol / L); C chlorine is the chlorine consumption for 20 minutes;

[0119] The concentration of carboxyl-containing substances in the actual water body is predicted as follows:

[0120] C carboxyl = 8.33 x 10 -6 C DOC (35)

[0121] In the formula, C carboxyl is the concentration of carboxyl-containing substances in the actual water body (mol / L); C DOC is the concentration of dissolved organic carbon in the actual water body (mg / L);

[0122] Step 4: Further, the reaction rate of the generation of different disinfection by-products obtained in step (2) and the concentration of reactants obtained in step (3) are input into the established model, and the NOM dec Such substances do not contribute to the generation of disinfection by-products, so the concentration of such substances is referred to the concentration of such substances in the natural organic matter standard (4.8 x 10 -5 M), and finally the disinfection by-product generation kinetics model of the actual water body is obtained by fitting calculation. Water samples are collected from drinking water sources in three different river basins in the country for preliminary water quality analysis, and then the dissolved organic carbon concentration of the water sample is diluted to 2 mg / L, and the initial concentration of hypochlorous acid for disinfection is set to 10 mg / L. The disinfection by-product generation kinetics experiment is carried out for 48 hours. Then, according to the above embodiment, the fitting results of the disinfection by-product generation kinetics of the actual water body are as shown in Figure 4 、 Figure 5 The above results show that the design of the present application is reasonable, and the prediction of the disinfection by-product generation kinetics of the actual water body is accurate.

[0123] The above embodiments are only used to illustrate the principles and specific ways of the present application, so that those skilled in the art can understand and apply the present application, and are not used to limit the scope of the specific embodiments of the present application, and modifications and changes made without departing from the spirit and technical ideas of the present application, and the inventions using the concept of the present application, should be covered by the claims of the present application.

Claims

1. A method for predicting the formation of disinfection by-products in drinking water based on a reaction kinetics model, characterized in that, It comprises the following steps: 1) constructing a disinfection by-product generation kinetics model of model compounds and determining the reaction rate of each step; 2) constructing and optimizing a disinfection by-product generation kinetics model of natural organic matter to obtain a disinfection by-product generation kinetics model of an actual water body; 3) establishing a method for measuring the concentration of each component of the reactant in the disinfection by-product generation kinetics model; 4) inputting the measured concentration of each component in the actual water body into the constructed model to calculate and predict the disinfection by-product generation kinetics result of the actual water body.

2. The method for rapid prediction of disinfection by-product concentration in drinking water according to claim 1, characterized in that, The disinfection by-product generation kinetics model of model compounds is constructed and the reaction rate of each step is determined: In the present application, seven different model compounds are selected to represent the precursors of disinfection by-products in an actual water body for disinfection by-product generation kinetics experiments, a model is constructed by using Kintecus software, and the rate of each reaction step of different model compounds is obtained by fitting the disinfection by-product generation kinetics experiment result of the model compound; The reaction model of the model compound and the disinfectant comprises the following steps: MC + HOX→ Pre (1) Pre + HOX→DBPs (2) MC + HOX→Pro (3) DBPs→DBPs, hy (4) DBPs + HOX→DBPs, pro (5) In the formula, MC represents the seven model compounds described in step 1); HOX represents two disinfectants, hypochlorous acid and hypobromous acid, which represent the generation process of chlorinated disinfection by-products and brominated disinfection by-products when bromide ions exist, respectively; Pre represents the precursors of disinfection by-products generated by the reaction of the model compound and the disinfectant; Pro represents other non-disinfection by-product products generated by the reaction of the model compound and the disinfection by-product, and the generation reaction of these products and the generation reaction of the disinfection by-product are competitive reactions; DBPs, hy represents the hydrolysis product of the disinfection by-product; and DBPs, pro represents the oxidation product of the disinfection by-product.

3. The method for rapid prediction of disinfection by-product concentration in drinking water according to claim 1, characterized in that, The disinfection by-product generation kinetics model of natural organic matter is constructed and optimized to obtain the disinfection by-product generation kinetics model of the actual water body: In the present application, natural organic matter is selected for disinfection by-product generation kinetics experiments, the natural organic matter is classified based on the type of the model compound in claim 1, a model is constructed by using Kintecus software, and the fitting result is obtained by the disinfection by-product generation kinetics experiment result of the natural organic matter, and the disinfection by-product generation kinetics model of the actual water body is obtained based on the optimization of the fitting result and the reaction rate of each step in claim 1; The disinfection by-product generation kinetics model of the actual water body comprises the following steps: Br - + HOCl → HOBr + Cl - (6) NOM phenolic + HOCl → Pre (7) Pre + HOCl→Cl-DBPs (8) NOM phenolic + HOCl → Pro (9) NOM phenolic + HOBr → Pre (10) Pre + HOBr→Br-DBPs (11) NOM phenolic + HOBr → Pro (12) NOM carboxyl + HOCl → Pre (13) Pre + HOCl→Cl-DBPs (14) NOM carboxyl + HOCl → Pro (15) NOM carboxyl + HOBr → Pre (16) Pre + HOBr→Br-DBPs (17) NOM carboxyl + HOBr → Pro (18) NOM AAs + HOCl → Pre (19) Pre + HOCl→Cl-DBPs (20) NOM AAs + HOCl → Pro (21) NOM AAs + HOBr → Pre (22) Pre + HOBr→Br-DBPs (23) NOM AAs + HOBr → Pro (24) NOM dec + HOCl → Pro (25) NOM dec + HOBr → Pro (26) Cl-DBPs→DBPs, hy (27) Br-DBPs + HOBr → DBPs, pro (32) Cl-DBPs + HOCl → DBPs, pro (29) Cl-DBPs + HOBr → DBPs, pro (30) Br-DBPs + HOCl → DBPs, pro (31) Br-DBPs + HOBr → DBPs, pro (32) wherein NOM phenolic represents phenolic substances in natural organic matter; Cl-DBPs represent chlorinated disinfection by-products; Br-DBPs represent brominated disinfection by-products; NOM carboxyl represents carboxylic substances in natural organic matter; NOM AAs represents amino acid (organic nitrogen) substances in natural organic matter; NOM dec represents substances in natural organic matter that react with disinfectants but do not generate disinfection by-products, and these substances compete with the reaction of disinfectants and the generation of other disinfection by-products; DBPs,pro represents the products generated by the reaction of disinfection by-products with disinfectants.

4. The method for rapid prediction of drinking water disinfection by-product concentration according to claim 1, characterized in that, The method for predicting the concentration of each component of the reactants in the establishment of the disinfection by-product generation kinetics model comprises the following steps: In the present application, the linear relationship between the concentration of phenolic substances and the absorbance at 254 nm ultraviolet wavelength, the linear relationship between the concentration of amino acids (organic nitrogen) in the actual water body and the consumption of disinfectant in the disinfection process (20 minutes), and the concentration of carboxyl-containing substances are predicted according to the proportion of the carboxyl-containing substances in the dissolved organic carbon.

5. The method for rapid prediction of drinking water disinfection by-product concentrations of claim 1, wherein, Based on the concentrations of each component of the actual water body obtained from claim 4, the actual water body disinfection by-product generation kinetics model constructed in claim 3 is input, and the predicted actual water body disinfection by-product generation kinetics result is obtained through model calculation fitting.

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