A method for predicting sludge bulking by integrating the risks of sludge volume and toxicity effects in a wastewater treatment process using a risk induction score

Abstract

The present application belongs to the technical field of sewage treatment risk early warning, and discloses a method for predicting sludge bulking by integrating sludge volume and toxicity effect in a sewage treatment process, which comprises the following steps: S1. calculating RIS according to the integrated sludge biological effect index and physicochemical index; the RIS is the product of the sludge functional enzyme biological index (the ratio of the maximum effect concentration to the half effect concentration) and the physicochemical index (the ratio of the measured SVI value to the limited SVI value of sludge bulging); S2. defining the safe range of sludge bulging under the RIS according to the risk event probability statistics, and defining the success event and the failure event as RIS<2 and RIS>2 respectively; MOS=L * N max ‑(LN max ‑Z risk S * )=Z risk S * (5) wherein: S * : the standard deviation of the process index of the sewage plant; Z risk : the standard normal quantile of any specified acceptable risk level, and the value is obtained by consulting the normal distribution table; the evaluation result of the present application is high in accuracy, and to a certain extent, prevents the limitations brought by sludge bulging faced by the sewage treatment process system.

Description

Technical Field

[0001] This invention belongs to the field of wastewater treatment risk early warning technology, and relates to the different responses of sludge functional enzymes to new active pollutants in urban wastewater treatment processes, and to the early warning of the risk of sludge bulking in wastewater treatment. Specifically, it relates to a method for predicting sludge bulking by integrating the risk-induced fraction of sludge volume and toxicity effect in wastewater treatment processes. Background Technology

[0002] Activated sludge treatment is a commonly used method for urban wastewater treatment. In the activated sludge process, microorganisms aggregate together in the form of flocs. The formation of sludge flocs is crucial for the operation of the activated sludge process, allowing the sludge to participate in the degradation reaction of wastewater and then separating the treated wastewater from the flocs through sedimentation. Although the aggregation of numerous microorganisms forms activated sludge flocs, they are highly susceptible to external influences. Environmental changes exceeding the flocs' tolerance can easily lead to floc disintegration and sludge bulking. Currently, the incidence of sludge bulking is relatively high in activated sludge treatment processes in urban wastewater treatment plants. Sludge bulking not only causes sludge loss from the water body and results in effluent quality exceeding standards, but it can also cause significant damage to the entire wastewater treatment system. Therefore, early warning of sludge bulking risks and ensuring the stability of the wastewater treatment system are crucial steps in achieving water quality standards.

[0003] During the formation of activated sludge flocs, a type of microorganism plays a crucial role. These microorganisms, resembling hair strands, are called filamentous bacteria. Excessive proliferation of filamentous bacteria within the flocs easily leads to filamentous bulking. In actual operation, many factors influence filamentous sludge bulking, including sludge concentration in the aeration tank, sludge settling ratio (SV), sludge volume index (SVI), retention time, dissolved oxygen, and influent pollutant concentration. SVI is often used as the criterion for judging sludge bulking. On the other hand, sludge performance indicators in biological treatment tanks can also be reflected by microbial activity. The activity of functional enzymes in sludge flocs largely reflects the activity state of sludge microorganisms. Different proliferation rates of microbial communities lead to changes in the rate of organic matter metabolism; a slower metabolic rate can cause non-filamentous sludge bulking.

[0004] In summary, this invention proposes a risk-inducible score that integrates sludge volume and toxicity effects in wastewater treatment processes, which can provide early warning of sludge bulking risks caused by filamentous or non-filamentous bacteria. Summary of the Invention

[0005] To overcome the shortcomings of existing technologies, this invention achieves risk control of wastewater treatment systems by identifying the safety boundary values ​​of process parameters in wastewater treatment plants.

[0006] This invention proposes to use relevant data on sludge bulking and biochemical indicators such as sludge functional enzymes to consider the toxic effects of pollutants on the microbial treatment efficiency of sludge, comprehensively evaluate the risk of sludge bulking, and regulate influencing factors to keep the RIS of this invention within an optimal range, thereby more intuitively controlling the effluent quality to meet discharge standards and improving the operating efficiency of the process.

[0007] Activated sludge in its endogenous metabolic phase generally has a lower RIS value, while activated sludge in its growth phase has a higher RIS value. RIS primarily reflects the concentration of the mixed liquor in the biological treatment tank. Changes in RIS indicate the properties of the activated sludge and the oxygen supply in the tank. The RIS index can also be used to determine the amount of excess sludge discharged, thereby controlling the sludge concentration in the tank, providing early warning of sludge bulking, and ensuring effluent quality. This invention shifts the focus from simply judging the severity of sludge bulking to proactively addressing the issue at its source, thus eliminating potential risks.

[0008] SVI (Self-Identification Index) is commonly used to determine whether activated sludge bulking has occurred. However, controlling the increase or decrease of filamentous bacteria solely through SVI technology does not always yield good results, as the relationship between them is variable. Therefore, we introduce the RIS (Reactive Protein Response) method, which combines chemical indicators with the stress response of sensitive functional enzymes to provide early warning of sludge bulking risk.

[0009] In wastewater treatment systems, biomarkers include not only various bacterial communities but also microbial functional enzymes. The oxidative decomposition of organic pollutants in wastewater occurs under the catalytic action of microbial enzymes, such as catalase, laccase, nitrate reductase, urease, and dehydrogenase. These enzymes play a crucial role in wastewater purification, and their activity reflects the quality of sludge performance. By exploring the responses of sludge functional enzymes to biochemical indicators, the likelihood of sludge bulking can be assessed from multiple dimensions.

[0010] The activity level of dehydrogenases directly affects the operational efficiency of biological treatment facilities, and they have the advantages of being simple, sensitive, and reliable compared to other hydrolytic enzymes. Therefore, TCEP, a representative new pollutant, was selected to measure the dehydrogenase activity of aerobic sludge and its changes in sludge activity under stress.

[0011] To achieve the above objectives, the technical solution of the present invention is as follows:

[0012] A method for predicting sludge bulking using risk-induced fractions of sludge volume and toxicity effects in an integrated wastewater treatment process includes the following steps:

[0013] 1. Calculate the RIS based on the integrated measured sludge biological effect indicators and physicochemical indicators.

[0014] RIS is a biological indicator of sludge functional enzymes (the ratio of maximum effective concentration to half-maximal effective concentration) and a physicochemical indicator (the measured SVI value and the limit SVI for sludge bulking). * The product of the ratios of values, SVI is measured in mL / g. Generally, SVI... * The value is 200 mL / g;

[0015] Where E max (mol / L) and EC 50 (mol / L) represents the maximum effective concentration and half-maximal effective concentration in the assay of dehydrogenase activity, determined by measuring the dehydrogenase activity ratio E. max / EC 50 To characterize the impact on sludge performance.

[0016]

[0017]

[0018] 2. Define the safe range of sludge bulking under RIS.

[0019] Based on the probability statistics of risk events, successful events (system meets the standard) and failure events (system does not meet the standard) can be defined as RIS<2 and RIS>2, respectively.

[0020] MOS can be defined as the maximum limit value (LN) for the design of process parameters in wastewater treatment plants. max Related loads and critical values ​​LN critical The difference between the relevant loads defines a failure event as an event in which the process parameters of the wastewater treatment plant exceed the system design limits.

[0021] MOS = LN max -LN critical (3)

[0022] Risk is defined as failure events RIS > 2, defined as follows:

[0023] Where p(RIS) is the probability density function of RIS, which can be assumed to follow a normal distribution, with a critical value of LN. critical It can be considered as the difference between the maximum limit concentration and the risk value. Therefore, when the process indicators of the wastewater treatment plant are normally distributed, it can be calculated using equation (5):

[0024] MOS = LN max -(LN max -Z risk S * ) = Z risk S * (5)

[0025] In the formula: S * Standard deviation of process parameters in wastewater treatment plants;

[0026] Z risk The standard normal quantile for any specified acceptable risk level can be obtained from a table.

[0027] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0028] This invention applies the safety boundary values ​​of wastewater treatment plant process indicators to provide a method for comprehensively evaluating sludge bulking. The evaluation results are highly accurate and, to a certain extent, prevent the limitations caused by sludge bulking in wastewater treatment process systems. Attached Figure Description

[0029] Figure 1 This is a trend curve of SVI;

[0030] Figure 2 This is a graph showing the inhibition rate of TCEP on dehydrogenase activity.

[0031] Figure 3 It is a graph showing the change in sludge performance under toxic conditions;

[0032] Figure 4 This is a normal distribution plot of RIS obtained from 10 samplings. Detailed Implementation

[0033] The present invention is described in detail below through specific embodiments, but this does not limit the scope of protection of the present invention. Unless otherwise specified, the experimental methods used in the present invention are all conventional methods, and the experimental equipment, materials, reagents, etc. used can all be obtained commercially.

[0034] Example 1

[0035] The physicochemical properties of wastewater in urban wastewater treatment plants can be obtained by consulting literature, and detailed information is shown in Table 1. The trend of SVI over time is shown in... Figure 1 As shown.

[0036] Table 1 Physicochemical Properties of Sludge

[0037]

[0038] The activity of sludge dehydrogenase (TCEP) was determined using the 2,3,5-triphenyltetrazolium chloride (TTC) method. Sludge suspensions were prepared by mixing sludge with different concentration gradients of pollutant solutions at a volume ratio of 100:1. The TCEP concentration range was 0–70 ng / L, with a concentration gradient of 10 ng / L. For the assay, two 25 mL stoppered centrifuge tubes were used. 0.5 mL of Na₂S solution, 2.0 mL of Tris-HCl buffer, 2 mL of sludge suspension, and 0.5 mL of 0.4% TTC solution were added sequentially to each tube (0.5 mL of deionized water was added to the control group). The tubes were sealed and shaken well, then immediately incubated at 37 °C for 10 min. 0.5 mL of formaldehyde was added to terminate the reaction. Finally, 5 mL of acetone was added to each tube, and the mixture was incubated at 37 °C for 10 min. After cooling to room temperature, the tubes were centrifuged at 4000 rpm for 5 min, and the absorbance of the supernatant at 485 nm was measured. The corresponding TTC concentration was calculated. Each group has 3 parallel samples, and each sample is measured 5 to 7 times. The relative standard deviation is controlled within 5%.

[0039] Dehydrogenase activity can be calculated according to formula (6):

[0040] Dehydrogenase activity = A * B * C (6)

[0041] Where: A is the TTC concentration (μg·mL) obtained from the standard curve based on the absorbance value. -1 A is the incubation time correction value (h); B is the dilution factor for colorimetric analysis. When the value of A exceeds 0.8, reasonable dilution should be performed to ensure the effectiveness of the standard curve.

[0042] In this invention, the effect of the compound on the dehydrogenase is expressed as the relative change rate (inhibition rate) (R) of enzyme activity. The calculation method is given by formula (7), where An is the enzyme activity value at a certain exposure concentration; A0 is the enzyme activity value of the blank control.

[0043]

[0044] Figure 2 The graph shows the variation in the inhibition rate of TCEP on dehydrogenase activity at different concentrations. From the graph, we can see the EC50 of TCEP on sludge dehydrogenase activity. 50 9.20×10 -11 mol / L and E max 1.75×10 -10 mol / L. Figure 3 The variation of sludge performance RIS under toxic conditions was shown in 10 sampling tests. The mean RIS value of the 10 sampling tests was 2.985, and the standard deviation was 1.103.

[0045] Since RIS > 2 is a fault event, the maximum RIS value greater than 2 in 10 samples is taken as the upper limit, so the range of RIS is set to (2, 5.1585).

[0046]

[0047]

[0048] Find Z from the normal distribution table risk =0.6368

[0049] MOS = 0.6368 × 1.103 = 0.702

[0050] L = LN max -MOS = 2 - 0.702 = 1.298 ≈ 1.30

[0051] Therefore, the security boundary range of RIS is 1.30 to 2.00, i.e. Figure 4 The area between the two solid blue lines, and the red area, represents the risk zone. When 1.30 > RIS > 0, the sludge flocs are considered small, containing more inorganic matter, and the sludge activity is poor. When RIS is greater than 2.00, the sludge is significantly affected by toxic substances, leading to sludge poisoning, poor settling performance, and a high risk of sludge bulking. Therefore, the safe range for sludge bulking is 1.30. <RIS<2.00。

[0052] The RIS method not only considers the physicochemical properties of sludge but also comprehensively assesses the impact of pollutant toxicity on sludge. Experiments have determined the safe range of the RIS, which has scientific significance for early warning of sludge bulking risk. Therefore, using the RIS method to prevent sludge bulking complies with national standards and has a certain scientific basis.

[0053] The embodiments described above are merely preferred embodiments of the present invention, and not all feasible embodiments of the present invention. Any obvious modifications made by those skilled in the art without departing from the principles and spirit of the present invention should be considered to be included within the scope of protection of the claims of the present invention.

Claims

1. A method for predicting sludge bulking using risk-induced fractions of sludge volume and toxicity effects in an integrated wastewater treatment process, characterized in that, Includes the following steps: S1. RIS is calculated based on the integrated measured sludge biological effect indicators and physicochemical indicators. RIS is the product of the sludge functional enzyme biological indicator and the physicochemical indicator. The sludge functional enzyme biological indicator is the ratio of the maximum effective concentration to the half-maximum effective concentration, and the physicochemical indicator is the measured SVI value and the limit SVI for sludge bulking. * The ratio of values, SVI is measured in mL / g. * The value is 200 mL / g; RIS= (1) ALL(mL / g)= (2) Where E max With EC 50 These are the maximum effect concentration and half-maximal effect concentration (MCI) in the assay of dehydrogenase activity, both in mol / L. The dehydrogenase activity ratio E is determined by measuring the MCI. max / EC 50 To characterize the impact on sludge performance; S2. Based on the probability statistics of risk events, the safe range of sludge bulking under RIS is defined, and successful events and failure events are defined as RIS<2 and RIS>2, respectively. MOS=LN max -(LN max -Z risk S * )= Z risk S * (5) In the formula: S * Standard deviation of process parameters in wastewater treatment plants; Z risk : The standard normal quantile for any specified acceptable risk level, obtained by looking up the normal distribution table; LN max The maximum limit value of the process parameters designed for wastewater treatment plants.

2. The method for predicting sludge bulking using sludge volume and risk-induced fractions of toxicity effects in the integrated wastewater treatment process as described in claim 1, characterized in that, In step S2: Equation (5) is derived in the following way: MOS=LN max -LN critical (3) The risk is defined as P(RIS>2) = 2 failure events. (4) Where p(RIS) is the probability density function of RIS, RIS is assumed to be normally distributed, and the critical value is LN. critical It is considered to be the difference between the maximum limit concentration and the risk value.

3. The method for predicting sludge bulking using the risk-induced fraction of sludge volume and toxicity effects in the integrated wastewater treatment process as described in claim 1, characterized in that... EC in step S1 50 and E max The results were obtained by analyzing the changes in the inhibition rate of dehydrogenase activity at different concentrations of TCEP.

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