Feedback type prediction method for optimizing ultraviolet / chlorine degradation odor substances

Abstract

The invention discloses a feedback type prediction method for optimizing ultraviolet / chlorine degradation odor substances, which comprises the following steps: for a water body which is subjected to degradation treatment by adopting an ultraviolet / chlorine oxidation process, obtaining the steady-state concentration of active free radicals in the water body; based on the obtained steady-state concentration of the active free radicals, establishing a kinetic model for degrading the odor substances by the ultraviolet / oxychlorination process, and predicting the effect of degrading the odor substances by the ultraviolet / oxychlorination process; the water body contains bicarbonate ions, chloride ions and soluble organic carbon, the content of bromide ions in the water body is less than or equal to 1 mu mol / L, and the content of ammonium ions in the water body is less than or equal to 1 mu mol / L. According to the prediction method disclosed by the invention, aiming at a specific water body which is subjected to degradation treatment by adopting an ultraviolet / oxychlorination process, the effect of degrading the odor substances by adopting the ultraviolet / oxychlorination process can be well predicted through the prediction method, and then feedback type optimization adjustment of degrading the odor substances by adopting the ultraviolet / oxychlorination process can be realized by adjusting process parameters.

Description

Technical Field

[0001] The present invention belongs to the technical field of environmental detection and treatment, and in particular relates to a feedback-type optimization prediction method for ultraviolet / chlorine degradation of odorous substances. Background Art

[0002] Odor compounds are a major factor affecting water quality. Common odorants include 2-methylisoborneol (2-MIB) and geosmin (GSM). 2-MIB and GSM have extremely low odor thresholds (10 ng / L), producing musty and earthy odors and pungent odors at these levels. They are primarily secreted by a range of cyanobacteria, including Anabaena, and are the most common odorous compounds in algal blooms. During algal blooms, they impart a fishy odor, and concentrations exceeding the odor threshold (10 ng / L) can severely impact water supply. Because both 2-MIB and GSM possess highly stable saturated tertiary alcohol structures, low Henry's modulus, strong antioxidant properties, and steric hindrance, conventional drinking water treatment processes (coagulation, sedimentation, filtration, and disinfection) are difficult to effectively remove. Furthermore, their degradation by common oxidants (chlorine, chloramines, chlorine dioxide, potassium permanganate, etc.) is also limited.

[0003] Ultraviolet advanced oxidation technology (UV-AOP) is a highly promising deep-drinking water treatment technology with advantages such as high treatment efficiency, small footprint, ease of modification, and simple operation. It offers the advantage of flexible start-up and shutdown, particularly for addressing intermittent and sudden odor pollution. Among them, UV / hydrogen peroxide advanced oxidation technology has been applied in many water plants in my country, achieving excellent treatment results. The highly oxidizing hydroxyl radicals (OH·) generated in the system are highly reactive with odorous substances such as 2-MIB and GSM, with secondary reaction rate constants as high as 5.1×10 9 M -1 ·s -1 and 7.8×10 9 M -1 ·s -1 The UV / Cl2 advanced oxidation process is also a good UV advanced oxidation technology. Chlorine-containing substances (such as HOCl / OCl - ) is a common disinfectant used in water treatment to kill pathogenic microorganisms in water; however, due to the strong selectivity of chlorine in its reaction with new pollutants, chlorination treatment is not very effective in removing new pollutants. In the UV / Cl2 process, ultraviolet irradiation can directly photolyze chlorine to produce Cl· and HO·. Under ultraviolet conditions at 254nm, the molar absorption coefficient of HClO (ε 254 ) and quantum yield (Ф) are 62M -1 cm -1and 0.62 mol·E -1 , which is significantly better than H2O2; it will then further react to produce secondary free radicals (Cl2· – and ClO·); In addition, ClO - It can also photolyze to produce ground-state oxygen atoms (O( 3 P)), O( 3 P) can react with O2 to generate oxidant O3. Cl·、Cl2· – and ClO· are collectively referred to as chlorine reactive species (RCS), and their redox potentials are 2.4V, 2.0V, and 1.5-1.8V, respectively. The oxidizing capacity of Cl· is similar to that of HO· and SO4· - The two are comparable, and the reaction rate constants with new pollutants are mostly between 10 8 M -1 ·s -1 to 10 10 M -1 ·s -1 This makes it one of the most oxidizing active species in the water environment.

[0004] In the actual engineering application of UV / chlorine advanced oxidation process to degrade odorous substances, a major challenge is to monitor the degradation efficiency of odorous substances in real time. Accurate and real-time understanding of the degradation efficiency can accurately control the dosage of UV and oxidants. However, this challenge is even more difficult in actual applications in real water bodies: most odorous substances in water exist in trace concentrations (ng / L), and online monitoring is expensive, time-consuming, or even impossible. Constructing a model to fit and predict the degradation of odorous substances is a fast and low-cost solution. At present, some studies have achieved varying degrees of success on a laboratory scale. However, the oxidant consumption, oxidant photolysis, and various free radical reactions in the UV / chlorine advanced oxidation system in real water bodies are highly complex. In addition, the water quality of real water bodies often changes with time and space, which also increases the difficulty of model prediction.

[0005] Furthermore, model predictions often require determining the steady-state concentrations of various free radicals in the UV / chlorine advanced oxidation system. Existing methods can be broadly categorized into two types: The first involves the probe method, which utilizes the differences in the reactivity of different probe substances with the various free radicals in the UV / chlorine advanced oxidation system to monitor the decay of the probe substances. The steady-state concentration of free radicals in the UV / chlorine advanced oxidation system can be calculated by calculating the decay kinetics. The second involves model prediction. Currently, the reaction kinetics of pollutants in UV / chlorine advanced oxidation systems have been extensively studied. Knowing the specific reaction equations and corresponding chemical reaction rates allows the steady-state concentration of free radicals in the UV / AOPs system to be calculated through model prediction. However, in pilot-scale experiments using actual water bodies as the target, the probe compounds used in the probe method (such as nitrobenzene) are generally highly volatile, making it difficult to maintain a closed environment at the pilot scale. The strong volatility of the probe compounds makes it difficult to accurately monitor their decay kinetics. As for the model prediction method, due to the complex reactions and numerous influencing factors in actual water bodies, determining the appropriate prediction model and related parameters is an important prerequisite for accurate prediction. However, there is currently a lack of relevant prediction research on actual water bodies at the pilot scale. Summary of the Invention

[0006] In order to overcome at least one of the problems existing in the above-mentioned prior art, one of the objectives of the present invention is to provide a feedback-type optimization prediction method for UV / chlorine degradation of odorous substances.

[0007] A second object of the present invention is to provide a method for feedback optimization of ultraviolet / chlorine degradation of odorous substances.

[0008] In order to achieve the above object, the technical solution adopted by the present invention is:

[0009] A first aspect of the present invention provides a feedback-optimized prediction method for UV / chlorine degradation of odorous substances, comprising the following steps: obtaining a steady-state concentration of active free radicals in a water body subjected to degradation treatment using a UV / chlorine oxidation process; establishing a kinetic model for the degradation of odorous substances by the UV / chlorine oxidation process based on the obtained steady-state concentration of active free radicals, and predicting the effectiveness of the UV / chlorine oxidation process in degrading odorous substances;

[0010] The water body contains bicarbonate ions, chloride ions and dissolved organic carbon, and the bromide ion content in the water body is ≤1 μmol / L, and the ammonium ion content in the water body is ≤1 μmol / L.

[0011] Since bromide ions and ammonium ions will affect the prediction accuracy of the prediction method of the present invention, the method of the present invention is suitable for water bodies with low bromide ion and ammonium ion content, or without bromide ions and ammonium ions, and uses a UV / chlorine oxidation process to degrade odorous substances in this type of water body. Based on the prediction method of the present invention, the effect of the UV / chlorine oxidation process on the degradation of odorous substances can be well predicted, and then by adjusting the process parameters of the UV / chlorine oxidation process, feedback optimization adjustment of the UV / chlorine oxidation process on the degradation of odorous substances can be achieved.

[0012] In some embodiments of the present invention, the bromide ion content in the water body is 0-1 μmol / L; for example, it can be any one of 0 μmol / L, 0.1 μmol / L, 0.3 μmol / L, 0.5 μmol / L, 0.8 μmol / L or 1 μmol / L, or a range value between any two of them.

[0013] In some embodiments of the present invention, the ammonium ion content in the water body is 0-1 μmol / L; for example, it can be any one of 0 μmol / L, 0.1 μmol / L, 0.3 μmol / L, 0.5 μmol / L, 0.8 μmol / L or 1 μmol / L, or a range value between any two of them.

[0014] In some embodiments of the present invention, the bicarbonate ion content in the water body is ≥0.5mmol / L; in some specific embodiments of the present invention, the bicarbonate ion content in the water body is 0.5-10mmol / L; for example, it can be any one of 0.5mmol / L, 0.8mmol / L, 1mmol / L, 1.2mmol / L, 1.5mmol / L, 2mmol / L, 5mmol / L, 8mmol / L or 10mmol / L, or a range value between any two of them.

[0015] In some embodiments of the present invention, the chloride ion content in the water body is ≥3 mg / L; in some specific embodiments of the present invention, the chloride ion content in the water body is 3-30 mmol / L; for example, it can be any one of 3 mg / L, 5 mg / L, 8 mg / L, 10 mg / L, 15 mg / L, 20 mg / L, 25 mg / L or 30 mg / L, or a range value between any two of them.

[0016] In some embodiments of the present invention, the dissolved organic carbon content in the water body is ≥1 mg / L; in some specific embodiments of the present invention, the dissolved organic carbon content in the water body is 1-20 mg / L; for example, it can be any one of 1 mg / L, 3 mg / L, 5 mg / L, 8 mg / L, 10 mg / L, 12 mg / L, 15 mg / L or 20 mg / L, or a range value between any two of them.

[0017] In some embodiments of the present invention, the pH value of the water body is ≥7; in some specific embodiments of the present invention, the pH value of the water body is 7-10; for example, it can be any one of 7, 7.5, 8, 8.5, 9, 9.5 or 10 or a range value between any two of them.

[0018] In some embodiments of the present invention, the water body is an actual water body.

[0019] Compared with the water bodies studied in the laboratory, the oxidant consumption, oxidant photolysis and various free radical reactions in the UV / chlorine advanced oxidation process in actual water bodies are highly complex, and the water quality of actual water bodies often changes with time and space. These all increase the difficulty of model prediction of actual water bodies. The prediction method of the present invention can predict actual water bodies and achieve a high prediction accuracy.

[0020] In some embodiments of the present invention, the active free radicals include OH·, Cl·, Cl2· - and CO3· - .

[0021] In some embodiments of the present invention, the odorous substance includes at least one of saturated alicyclic alcohols, thioethers, pyrazines, thiazoles or terpenes; in some specific embodiments of the present invention, the odorous substance is selected from saturated alicyclic alcohols.

[0022] In some embodiments of the present invention, the saturated alicyclic alcohol substance includes 2-methylisoborneol (2-MIB) and / or geosmin (GSM); in some specific embodiments of the present invention, the saturated alicyclic alcohol substance is 2-methylisoborneol (2-MIB).

[0023] The prediction method of the present invention is applicable to various odorants, with particularly good prediction results for saturated alicyclic alcohols, particularly 2-MIB and GSM. In some practical prediction processes of the present invention, the present invention has particularly good prediction results for 2-MIB, as the reactive free radicals (such as Cl·) generated in water by the UV / chlorine oxidation process react more rapidly with 2-MIB, making the transient absorption and reaction rate constant of the reaction easier to measure.

[0024] In some embodiments of the present invention, the method for obtaining the steady-state concentration of active free radicals in water includes Kintecus model prediction.

[0025] In the pilot experiment with actual water bodies as the target water bodies, the present invention adopts the Kintecus model prediction method to well predict the steady-state concentration of each active free radical in the actual water body ([radical] ss ).

[0026] In some embodiments of the present invention, the input parameters predicted by the Kintecus model include UV dose, chlorine dosage, degradation treatment time, water pH value, bicarbonate ion content in the water, chloride ion content in the water, and dissolved organic carbon content in the water.

[0027] By selecting appropriate input parameters, the prediction model can be ensured to have a higher prediction accuracy; in addition, UV dose, chlorine addition amount, degradation treatment time, etc. are adjustable process parameters of the UV / chlorine oxidation process. By inputting and adjusting these process parameters, the degradation treatment effect can be predicted under the simulation state, thereby providing guidance for the actual degradation process.

[0028] In some embodiments of the present invention, the parameters for establishing the kinetic model also include the reaction rate constant (k radical，MP ), the reaction rate constant of odor substances oxidized by oxidants (k Ox，MP ) and the reaction rate constant (k UV，MP ).

[0029] In some embodiments of the present invention, the expression of the kinetic model is:

[0030] k′=∑(k radical，MP ×[radical] ss )+k ox，MP +k UV , MP (1);

[0031] R=1-e -k′t (2);

[0032] Where k′ is the pseudo-first-order reaction rate of the reaction system; k radical，MP is the reaction rate constant of active free radicals and odor substances; ss is the steady-state concentration of active free radicals; k Ox，MP k is the reaction rate constant of odorous substances being oxidized by oxidants; UV，MP is the reaction rate constant of the photolysis of odorous substances; R is the degradation rate of odorous substances; t is the degradation treatment time.

[0033] Formula (1) is derived from the pseudo-first-order kinetic formula The above-constructed kinetic model is simple and can accurately predict the effect of UV / chlorine oxidation process on the degradation of odorous substances by inputting various reaction rate constants and the steady-state concentration of active free radicals.

[0034] The second aspect of the present invention provides a method for feedback optimization of UV / chlorine degradation of odorous substances, comprising the following steps: using the prediction method described in the first aspect of the present invention to predict the effect of the UV / chlorine oxidation process on degrading odorous substances, thereby adjusting the process parameters of the UV / chlorine oxidation process, and based on the adjusted process parameters, using the UV / chlorine oxidation process to degrade the odorous substances.

[0035] Based on the prediction method of the present invention, a feedback-type optimization method for the degradation of odorous substances by UV / chlorine can be formed, thereby providing theoretical guidance for the adjustment of UV / chlorine advanced oxidation process parameters in actual production, improving the stability of the UV / chlorine oxidation process in degrading odorous substances; and forming empirical parameters to quickly respond to subsequent changes in water quality, effectively reducing the frequency of adjustment of process parameters, and reducing the process dosage and equipment loss.

[0036] In some embodiments of the present invention, the process parameters include at least one of UV dose, chlorine dosage, or degradation treatment time.

[0037] The beneficial effects of the present invention are as follows: the prediction method of the present invention is targeted at specific water bodies that are subjected to degradation treatment using an ultraviolet / chlorine oxidation process. The prediction method can well predict the effect of the ultraviolet / chlorine oxidation process on the degradation of odorous substances, and then, by adjusting the process parameters, feedback optimization adjustment of the ultraviolet / chlorine oxidation process on the degradation of odorous substances can be achieved. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] Figure 1 The present invention provides a technical roadmap for feedback optimization of the UV / chlorine degradation method for odorous substances in some embodiments of the present invention.

[0039] Figure 2 1 and 2-MIB. The transient absorption time curve and apparent rate equation curve of the reaction between Cl· and 2-MIB measured in some embodiments of the present invention are shown.

[0040] Figure 3 is the Cl2· measured in some embodiments of the present invention - Transient absorption time curve and apparent rate equation curve of reaction with 2-MIB.

[0041] Figure 4 The transient absorption time curve and apparent rate equation curve of the reaction between Cl· and GSM measured in some embodiments of the present invention are shown. DETAILED DESCRIPTION

[0042] The content of the present invention is further described in detail below through specific examples. It should be understood that the following examples are only used to further illustrate the present invention and cannot be interpreted as limiting the scope of protection of the present invention. Some non-essential improvements and adjustments made by those skilled in the art based on the principles set forth in the present invention all fall within the scope of protection of the present invention. The specific process parameters and the like in the following examples are only examples within a suitable range, and those skilled in the art can make selections within a suitable range through the description herein, and are not limited to the specific data exemplified below. The raw materials, reagents or devices used in the following examples and comparative examples, unless otherwise specified, can be obtained from conventional commercial sources, or can be obtained by existing known methods.

[0043] In some embodiments of the present invention, taking the odor substance 2-MIB as an example, the feedback optimization method of UV / chlorine degradation of odor substances can be found in Figure 1 The technical roadmap is as follows: by real-time monitoring of the effluent concentration of 2-MIB in the UV / chlorine advanced oxidation process as the main technical indicator, when the effluent concentration of 2-MIB does not meet the standard (greater than 10ng / L), the water quality analysis is carried out by detecting and collecting the real-time water body index parameters, such as DOC, alkalinity (in terms of HCO3 - The active free radicals (mainly OH·, Cl·, Cl2·) in the UV / chlorine advanced oxidation process under the water quality conditions were calculated by the prepared Kintecus software. - Br. - and CO3· - ) concentration, analyze the reasons why the 2-MIB effluent concentration does not meet the standard, and based on this, pre-adjust the reaction conditions of the UV / chlorine advanced oxidation process. The pre-adjustment parameters are input into the kinetic model to calculate and predict the 2-MIB effluent concentration. If the prediction meets the standard, the UV / chlorine advanced oxidation process parameters in actual production are adjusted according to the pre-adjustment parameters, and empirical parameters are formed in actual production operations to achieve rapid response to subsequent water quality changes. This method can effectively reduce the frequency of process parameter adjustments, as well as the process dosage and equipment loss.

[0044] In the UV advanced oxidation process, different oxidation systems will produce different active free radicals. In the current common UV advanced oxidation process for the degradation of odorous substances, the active free radicals that play a major role in the degradation of typical odorous substances (2-MIB) and geosmin (GSM) are OH·, SO4· - and Cl·, the relevant literature only reported some active free radicals (such as OH·, SO4· -The secondary reaction rate constants of ) with 2-MIB and GSM are shown in Table 1. - ) is an important part of the degradation of odorous substances by UV / chlorine advanced oxidation system. The relevant active chlorine radicals (Cl· and Cl2· - ) with 2-MIB and GSM.

[0045] According to relevant studies (such as LEI Y, LEI X, YU Y, et al. Rate Constants and Mechanisms for Reactions of Bromine Radicals with Trace Organic Contaminants [J]. Environ Sci Technol, 2021, 55(15): 10502-13), Cl· can be produced by the photolysis of chlorinated organic compounds. Among them, chloroacetone has a high molar absorptivity and quantum yield, which can ensure a strong Cl· signal and good data reproducibility.

[0046] In some embodiments of the present invention, chloroacetone is used as a Cl· precursor. Cl· is generated by chloroacetone (10 mM) excited by a 266 nm laser, and the secondary reaction rate of Cl· with 2-MIB is measured using free radical decay kinetics; persulfate (10 mM) is excited by a 266 nm laser to produce SO4· - , SO4· - With excess Cl - (0.5M) reaction produces Cl2· - , using free radical decay kinetics to measure Cl2· - The second-order reaction rate constant with 2-MIB. The excitation at 266 nm produces Cl· and Cl2· - The reaction was carried out with different concentrations of 2-MIB to obtain the following Figures 2-4 The decay curve of the free radicals and the linear relationship between the pseudo-first-order decay rate and the 2-MIB concentration, the slope is Cl·, Cl2· - Second-order reaction rate constants with 2-MIB or GSM.

[0047] Figure 2 Figure 3 is the transient absorption time curve and apparent rate equation curve of the reaction between Cl· and 2-MIB, where (a) is the transient absorption time curve and (b) is the apparent rate equation curve. Figure 3 Cl2· - Transient absorption time curve and apparent rate equation curve of the reaction with 2-MIB, where (a) is the transient absorption time curve and (b) is the apparent rate equation curve. Figure 4The transient absorption time curve and apparent rate equation curve of the reaction between Cl· and GSM, where (a) is the transient absorption time curve and (b) is the apparent rate equation curve. Figures 2-4 It can be seen that the secondary reaction rate constant of Cl· and 2-MIB, Cl2· - The secondary reaction rate constants of Cl· with 2-MIB and the secondary reaction rate constants of Cl· with GSM are shown in Table 1. - The secondary reaction rates with 2-MIB are k Cl·,2-MIB =6.0×10 9 M -1 ·s -1 、 The secondary reaction rate of Cl· with GSM is k Cl·,GSM =4.3×10 9 M -1 ·s -1 It should be noted that due to the Cl2· - The concentration is low, and Cl2· - The reaction rate with GSM is slow, making it difficult to measure Cl2· - and transient absorption of GSM responses.

[0048] Table 1 Second order reaction rate constants of active free radicals with 2-MIB and GSM (unit: M -1 ·s -1 )

[0049]

[0050] Note in Table 1: For data reported in the literature, see the following literature: (1) MAL, WANG C, LI H, et al. Degradation of geosmin and 2-methylisoborneol in water with UV / chlorine: Influencing factors, reactive species, and possible pathways [J]. Chemosphere, 2018, 211: 1166-75. (2) MENG T, SU X, SUN P. Degradation of geosmin and 2-methylisoborneol in UV-based AOPs for photoreactors with reflective inner surfaces:Kinetics and transformation products[J].Chemosphere,2022,306:135611.(3)ANTONOPOUULOU M,EVGENIDOU E,LAMBROPOULOU D,et al.A review on advanced oxidation processes for the removal of taste and odor compounds from aqueous media[J].Water Res,2014,53:215-34.(4)WANG D, BOLTON JR, ANDREWS SA, et al. UV / chlorine control of drinking water taste and odour at pilot and full-scale[J]. Chemosphere, 2015, 136: 239-44.

[0051] From the data in Table 1, we can see that the reactivity of OH· and Cl· with 2-MIB (10 9 M -1 ·s -1 ) than SO4· - Reactivity with 2-MIB (10 8 M -1 ·s -1 ) is one order of magnitude higher, and OH· and Cl· are the two main active species in the UV / chlorine advanced oxidation process, which also reflects the advantages of the UV / chlorine advanced oxidation process in degrading odor substances 2-MIB and GSM.

[0052] The following provides specific embodiments and comparative examples by taking Xijiang River water and raw water from a lake as examples to further illustrate the present invention.

[0053] Example 1

[0054] A feedback optimization prediction method for UV / chlorine degradation of odorous substances, the specific steps are as follows:

[0055] (1) Using Xijiang River water as experimental raw water, the UV / chlorine advanced oxidation process was used to degrade Xijiang River water on a pilot scale. The effluent concentration of 2-MIB in the UV / chlorine advanced oxidation process was monitored in real time as the main technical indicator. When the 2-MIB concentration in the process effluent did not meet the standard (greater than 10 ng / L), the water quality parameters of Xijiang River water (pH value, DOC, alkalinity, chloride ion, bromide ion, ammonium ion, etc.) and the process parameters of the UV / chlorine advanced oxidation process (UV dose, chlorine addition amount, degradation treatment time) were obtained in real time. The above water quality parameters and process parameters were input into Kintecus software to simulate the steady-state concentration of each active free radical in the UV / chlorine advanced oxidation system under actual water conditions. The water quality parameters of the experimental raw water in this case are shown in Table 2, and the predicted results of the steady-state concentration of active free radicals are shown in Table 3.

[0056] The process parameters of the UV / chlorine advanced oxidation process in this example are: UV dose = 1500mJ / cm 2 , Cl2 dosage = 3 mg / L, degradation treatment time is 330 s.

[0057] (2) Substituting the steady-state concentrations of the active free radicals in Table 3 and the secondary reaction rate constants in Table 4 into the kinetic model expression (1) can yield the pseudo-first-order reaction rate k' of 2-MIB degradation by the UV / chlorine advanced oxidation process. Substituting k' into expression (2) yields the predicted value of 2-MIB degradation efficiency.

[0058] The pilot test site used the same UV / chlorine advanced oxidation process conditions (UV dose = 1500mJ / cm 2 The actual 2-MIB degradation efficiency was measured using the following conditions (Cl₂ dosage = 3 mg / L, degradation treatment time = 330 s). The predicted values were compared with the actual values to determine the accuracy of the degradation efficiency prediction using this method. The predicted and actual test results for 2-MIB degradation efficiency in this example are shown in Table 5.

[0059] Expressions (1) and (2) are as follows:

[0060] k′=∑(k radical，MP ×[radical] ss )+k ox，MP +k UV, MP (1);

[0061] R=1-e -k′t (2);

[0062] Where R is the degradation rate of the odorous substance; k' is the pseudo-first-order reaction rate of the reaction system; t is the degradation treatment time; k radical，MP is the reaction rate constant of active free radicals and odor substances; ss is the steady-state concentration of active free radicals; k Ox，MP k is the reaction rate constant of odorous substances being oxidized by oxidants; UV，MP is the reaction rate constant of the photolysis of odorous substances.

[0063] The calculation formula for the degradation efficiency prediction accuracy is as follows:

[0064]

[0065] Specifically, the calculation process of the predicted value of the degradation efficiency of 2-MIB in this example is as follows:

[0066]

[0067] k UV =[(5.1×10 9 ×2.14×10 -13 +6.0×10 9 ×1.37×10 -14 +9.8×10 7 ×8.64×10 -13 +7.19×10 9 ×0+6.1×10 6 ×3.91×10 -10 )+5.91×10 -9 +5.90×10 -10 ]s -1 =3.64×10 -3 s -1 ;

[0068]

[0069] Comparative Example 1

[0070] A feedback optimization prediction method for UV / chlorine degradation of odorous substances. The difference from Example 1 is that the experimental raw water is different. The experimental raw water in this example is based on Xijiang water, and 50 μmol / L of Br is added. - ; The specific prediction method steps are the same as those in Example 1.

[0071] The water quality parameters of the raw water in this experiment are shown in Table 2; the predicted results of the steady-state concentration of active free radicals are shown in Table 3; and the predicted results and actual test results of the 2-MIB degradation efficiency and their comparison are shown in Table 5.

[0072] Comparative Example 2

[0073] A feedback optimization prediction method for UV / chlorine degradation of odorous substances. The difference from Example 1 is that the experimental raw water is different. The experimental raw water in this example is based on Xijiang water, and 50μmol / L NH4 is added + ; The specific prediction method steps are the same as those in Example 1.

[0074] The water quality parameters of the raw water in this experiment are shown in Table 2; the predicted results of the steady-state concentration of active free radicals are shown in Table 3; and the predicted results and actual test results of the 2-MIB degradation efficiency and their comparison are shown in Table 5.

[0075] Comparative Example 3

[0076] A feedback-optimized prediction method for ultraviolet / chlorine degradation of odorous substances is provided. The difference from Example 1 is that the experimental raw water is different. The experimental raw water in this example is raw water from a lake. The specific prediction method steps are the same as those in Example 1.

[0077] The water quality parameters of the raw water in this experiment are shown in Table 2; the predicted results of the steady-state concentration of active free radicals are shown in Table 3; and the predicted results and actual test results of the 2-MIB degradation efficiency and their comparison are shown in Table 5.

[0078] Table 2 Water quality parameters of experimental raw water in Example 1 and Comparative Examples 1 to 3

[0079]

[0080] Table 3 Prediction results of steady-state concentration of active free radicals in Example 1 and Comparative Examples 1 to 3

[0081]

[0082] Table 4 Secondary reaction rate constants involved in Example 1 and Comparative Examples 1 to 3 (unit: M -1 ·s -1 )

[0083]

[0084] Notes to Table 4: k Ox,2-MIB With k UV,2-MIB Based on actual measurements using UV lamps and oxidant (sodium hypochlorite) at the pilot site.

[0085] Table 5 Prediction results and actual test results and comparison of Example 1 and Comparative Examples 1 to 3

[0086]

[0087] As can be seen from Table 5, the predicted value of 2-MIB degradation efficiency in Example 1 of the present invention is very close to the actual value under the same conditions in the pilot test site, and the degradation efficiency prediction accuracy is high. + and Br - After that, the accuracy of the prediction model for the degradation rate of 2-MIB by UV / chlorine oxidation process dropped significantly. It can be seen that the prediction method of this model is suitable for water quality parameters with DOC, alkalinity, and chloride ion as the main characteristic parameters and NH4 + and Br - For water bodies with low odor content, the prediction of the degradation of odorous substances (such as 2-MIB) using the UV / chlorine oxidation process in this type of water body has a high accuracy. This method can especially provide theoretical data guidance for the degradation of 2-MIB by the UV / chlorine oxidation process in actual water bodies.

[0088] In summary, the present invention is based on a water body with bicarbonate ions, chloride ions and dissolved organic carbon as the main water quality characteristics, and with a low content of bromide ions and ammonium ions or no bromide ions and ammonium ions, and uses a UV / chlorine oxidation process to degrade odorous substances in this type of water body. By using the prediction method of the present invention, the effect of the UV / chlorine oxidation process on the degradation of odorous substances can be well predicted, and then by adjusting the process parameters of the UV / chlorine oxidation process, feedback optimization adjustment of the UV / chlorine oxidation process on the degradation of odorous substances can be achieved.

Claims

1. A feedback optimization prediction method for UV / chlorine degradation of odorous substances, characterized in that: The following steps are involved: For water bodies treated by UV / chlorine oxidation, the steady-state concentration of active free radicals in the water is obtained; based on the obtained steady-state concentration of active free radicals, a kinetic model for the degradation of odorous substances by the UV / chlorine oxidation process is established to predict the effect of the UV / chlorine oxidation process on the degradation of odorous substances; The water body contains bicarbonate ions, chloride ions and dissolved organic carbon, and the bromide ion content in the water body is ≤1 μmol / L, and the ammonium ion content in the water body is ≤1 μmol / L.

2. The prediction method according to claim 1, characterized in that The bicarbonate ion content in the water body is ≥0.5mmol / L; and / or, the chloride ion content in the water body is ≥3 mg / L; and / or, the dissolved organic carbon content in the water body is ≥1 mg / L; And / or, the pH value of the water body is ≥7.

3. The prediction method according to claim 1, wherein: The active free radicals include OH·, Cl·, Cl2· - and CO3· - .

4. The prediction method according to claim 1, wherein: The odorous substance includes at least one of saturated alicyclic alcohol substances, thioether substances, pyrazine substances, thiazole substances or terpenoid substances.

5. The prediction method according to claim 1, wherein: Methods for obtaining the steady-state concentration of active free radicals in water bodies include Kintecus model prediction.

6. The prediction method according to claim 5, characterized in that The input parameters predicted by the Kintecus model include UV dose, chlorine dosage, degradation treatment time, water pH, bicarbonate ion content in the water, chloride ion content in the water and dissolved organic carbon content in the water.

7. The prediction method according to claim 1, wherein: The parameters for establishing the kinetic model also include the reaction rate constant of the active free radicals with the odorous substance, the reaction rate constant of the odorous substance being oxidized by the oxidant, and the reaction rate constant of the odorous substance being photolyzed.

8. The prediction method according to claim 7, characterized in that The expression of the kinetic model is: R=1-e -k′t (2); Where k′ is the pseudo-first-order reaction rate of the reaction system; k radical，MP is the reaction rate constant of active free radicals and odor substances; ss is the steady-state concentration of active free radicals; k Ox，MP k is the reaction rate constant of odorous substances being oxidized by oxidants; UV，MP is the reaction rate constant of the photolysis of odorous substances; R is the degradation rate of odorous substances; t is the degradation treatment time.

9. A method for feedback optimization of UV / chlorine degradation of odorous substances, characterized in that: The following steps are involved: The prediction method described in any one of claims 1 to 8 is used to predict the effect of the UV / chlorine oxidation process on degrading odorous substances, thereby adjusting the process parameters of the UV / chlorine oxidation process, and based on the adjusted process parameters, the UV / chlorine oxidation process is used to degrade the odorous substances.

10. The method according to claim 9, characterized in that The process parameters include at least one of ultraviolet dosage, chlorine dosage or degradation treatment time.

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