Coupling regulation and control method for microbial community and environmental factors in sewage treatment plant

Abstract

The invention relates to the technical field of sewage treatment, and discloses a coupling regulation and control method for microbial communities and environmental factors in a sewage treatment plant. According to the method provided by the invention, samples are regularly collected in a period when the operation efficiency of a sewage treatment plant is stable, and reference data of functional bacteria genus are established, so that reliable reference standards are provided for later operation adjustment; various environmental factors such as COD (Chemical Oxygen Demand), DO (Dissolved Oxygen) and MLSS (Maximum Liquor Suspended Solid) of the inlet water are considered, and the correlation between the environmental factors and the abnormal bacteria genus is calculated through Spearman correlation analysis, so that the key environmental factors influencing the operation of the sewage treatment plant can be effectively identified.

Description

Technical Field

[0001] The present invention relates to the technical field of sewage treatment, and in particular to a method for coupling regulation of microbial communities and environmental factors in a sewage treatment plant. Background Art

[0002] Biological methods are widely used in urban sewage treatment plants in my country to treat sewage, and the optimization and stable operation of biological methods largely depend on the survival status of microorganisms. However, microorganisms are characterized by large numbers, small individuals, rich diversity, and poor culturability, which makes traditional culture methods present many challenges in microbial community research. Many functional microorganisms related to pollutant removal and sludge properties are difficult to observe using an optical microscope, which poses a great problem for the management of sewage treatment plants. With the increasingly stringent effluent water quality standards, sewage treatment plants urgently need to conduct in-depth research on the structure of microbial communities and correlate it with macro-indicators of system operation performance, thereby providing technical support for the efficient management of sewage treatment.

[0003] The rapid development of high-throughput sequencing technology has made it possible to comprehensively analyze the dynamic changes in microbial communities. The composition of the microbial community in sewage treatment plants directly affects the effluent quality. In short, the key to managing sewage treatment plants lies in the regulation of microorganisms. However, due to the lack of mature analytical methods and sufficient data accumulation, existing microbiological information has not been effectively applied to the operational diagnosis and management of sewage treatment. Current control methods in sewage treatment plants often rely on manual judgment of pollutant indicators, which is highly subjective and overly dependent on the experience of practitioners.

[0004] Direct observation often fails to reveal the interactions between microorganisms and organic pollutants, nitrogen, phosphorus, and other components in water. However, by monitoring fluctuations in environmental factors during treatment, the composition and abundance of microbial communities can be indirectly inferred. Therefore, wastewater treatment plants need to accumulate extensive data on microbial communities, identify functional microorganisms, and monitor environmental factors. By establishing correlations between environmental factors and the relative abundance of functional microorganisms, microbial survival can be more directly assessed, providing early warnings for water quality management and optimizing management decisions during treatment.

[0005] CN116797094A discloses a method and system for evaluating the water purification capacity of a sewage treatment plant. The method includes constructing a sewage treatment plant operational efficiency evaluation index system, which includes a basic water quality module, a sludge performance module, and a toxicology module. A comprehensive evaluation index is calculated for each module to accurately and intuitively assess the sewage treatment plant's operational efficiency. However, this method lacks microbial community data.

[0006] CN111595975A provides a water pollution analysis method and its application in water pollution monitoring and evaluation. The method uses urban sewage treatment plants and receiving rivers as research objects, demonstrates the correlation between environmental factors such as water temperature, ammonia nitrogen concentration and total phosphorus concentration and adenovirus, enterovirus and Krassler phage, and constructs a water pollutant evaluation method. However, the method has not played a role in optimizing the operating efficiency of sewage treatment plants. Summary of the Invention

[0007] The purpose of this invention is to solve the technical problem of how to optimize the sewage treatment effect by regulating the microbial community during the operation of existing sewage treatment plants, especially in biological sewage treatment.

[0008] In order to achieve the above objectives, the first aspect of the present invention provides a method for coupling regulation of microbial communities and environmental factors in a sewage treatment plant, the method comprising the following steps:

[0009] (1) Functional bacterial genera related to nitrogen and phosphorus pollutant removal and activated sludge settling performance in sewage treatment plants were selected as characteristic microbial communities;

[0010] (2) When the sewage treatment plant meets the corresponding discharge standards, regularly collect activated sludge samples throughout the year to determine the relative abundance range of functional bacterial genera and form a reference benchmark;

[0011] (3) When the operation of the sewage treatment plant becomes unstable, the characteristic microbial community structure described in step (1) is monitored, abnormal bacterial genera are screened out, and the correlation coefficient matrix between environmental factors and abnormal bacterial genera is calculated based on Spearman correlation analysis to identify environmental factors that are significantly correlated with the characteristic microbial community.

[0012] Preferably, in step (1), the functional bacteria are nitrifying bacteria, denitrifying bacteria, phosphate accumulating bacteria, denitrifying phosphate accumulating bacteria, filamentous bacteria and EPS secreting bacteria.

[0013] Further preferably, in step (2), the frequency of regularly collecting activated sludge samples throughout the year is once a month.

[0014] Preferably, in step (2), the relative abundance of functional bacterial genera is determined by using the screening condition of relative abundance > 0.01% in samples of at least one month to determine the variation range of the relative abundance of functional bacterial genera.

[0015] More preferably, in step (3), the unstable operation of the sewage treatment plant includes: the effluent TN does not meet the discharge standard, the effluent TP does not meet the discharge standard, or the activated sludge is in a micro-expansion state.

[0016] Preferably, in step (3), the abnormal bacterial genus is a bacterial genus that deviates from the relative abundance reference benchmark in step (2).

[0017] Further preferably, in step (3), the environmental factor is influent COD, influent TN, influent TP, DO, MLSS, MLVSS, ORP, pH, OUR, SRT or water temperature.

[0018] Preferably, in step (3), identifying an environmental factor significantly correlated with the microbial community is identifying an environmental factor having an absolute value of a correlation coefficient with the characteristic microbial community in step (1) close to 1 and a P value < 0.05.

[0019] The method provided by the present invention also has at least the following beneficial effects:

[0020] (1) By calculating the correlation between environmental factors and abnormal bacterial genera through Spearman correlation analysis, key environmental factors affecting the operation of sewage treatment plants can be effectively identified. This provides data support for the regulation and repair of sewage treatment plants, avoiding over-reliance on manual experience.

[0021] (2) Compared with the existing technology, the present invention focuses on the dynamic changes of microbial communities, closely combines the microbial community structure with the operating efficiency of sewage treatment plants, and provides a more targeted and practical technical solution for optimizing sewage treatment.

[0022] (3) By regularly collecting samples during the period when the sewage treatment plant's operating efficiency is stable and establishing baseline data for functional bacteria, a reliable reference standard can be provided for subsequent operational adjustments, ensuring that the system is always in optimal operating condition.

[0023] (4) This method takes into account multiple environmental factors such as influent COD, DO and MLSS, providing a more comprehensive means of wastewater treatment optimization, so that it can still play an effective role under complex environmental conditions. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Figure 1 This is a flow chart of the coupled regulation of microbial communities and environmental factors in a sewage treatment plant according to an embodiment of the present invention. DETAILED DESCRIPTION

[0025] The endpoints of the ranges and any values disclosed herein are not limited to the precise ranges or values, and these ranges or values should be understood to include values close to these ranges or values. For numerical ranges, the endpoints of each range, the endpoints of each range and individual point values, and the individual point values can be combined with each other to obtain one or more new numerical ranges, which should be considered to be specifically disclosed herein.

[0026] In the present invention, "influent COD" means influent chemical oxygen demand; "influent TN" means influent total nitrogen; "influent TP" means influent total phosphorus; "DO" means dissolved oxygen; "MLSS" means mixed liquor suspended solids; "MLVSS" means volatile suspended solids; "ORP" means oxidation-reduction potential; "OUR" means oxygen consumption rate; and "SRT" means sludge age.

[0027] The present invention will be described in detail below through examples. In the following examples, unless otherwise specified, the raw materials are all commercially available.

[0028] In the following examples, unless otherwise specified, when selecting characteristic microbial communities, all microbial communities were detected at once. The selected bacterial genera are related to the removal and sedimentation performance of nitrogen and phosphorus pollutants in the system, that is, to the operating efficiency of the system. The selection method is to consult the literature and determine the microbial species from the microbial community data provided by the sequencing platform.

[0029] Example 1

[0030] This example is used to provide a method for coupling regulation of microbial communities and environmental factors in a sewage treatment plant, and the method includes the following steps:

[0031] (1) Nitrifying bacteria, denitrifying bacteria, polyphosphate-accumulating bacteria, denitrifying polyphosphate-accumulating bacteria, filamentous bacteria and EPS-secreting bacteria were selected as characteristic microbial communities in a sewage treatment plant.

[0032] (2) During the period when the sewage treatment plant meets the corresponding discharge standards, collect activated sludge samples from the biological ponds at a frequency of once a month from June 2023 to June 2024 for high-throughput sequencing; analyze the sequencing results, and use the relative abundance > 0.01% in at least one month of samples as the screening condition to determine the relative abundance change range of the characteristic microbial community to form a reference benchmark;

[0033] In this embodiment, the reference standards of total nitrifying bacteria, total denitrifying bacteria, total phosphorus accumulating bacteria, total denitrifying phosphorus accumulating bacteria, total filamentous bacteria and EPS secreting bacteria are shown in Table 1.

[0034] (3) When the effluent TN of the sewage treatment plant does not meet the discharge standard, the characteristic microbial community structure described in step (1) is monitored, abnormal bacterial genera (bacterial genera that deviate from the reference benchmark in step (2)) are screened out, and the correlation coefficient matrix between environmental factors and the relative abundance of abnormal bacterial genera is calculated based on Spearman correlation analysis, and environmental factors with an absolute value of correlation coefficient close to 1 and a P value < 0.05 with the characteristic microbial community described in step (1) are identified, providing a scientific basis for the operation optimization and repair of the sewage treatment plant;

[0035] The environmental factors include influent COD, influent TN, influent TP, DO, MLSS, MLVSS, ORP, pH, OUR, SRT, and water temperature.

[0036] Example 2

[0037] This example is carried out according to the method of Example 1, except that in step (3), when the effluent TP of the sewage treatment plant does not meet the discharge standard, the structure of the characteristic microbial community described in step (1) is monitored. The remaining steps and parameters are the same as those of Example 1.

[0038] Example 3

[0039] This example is carried out according to the method of Example 1, except that in step (3), when the activated sludge of the sewage treatment plant is in a micro-expansion state, the structure of the characteristic microbial community described in step (1) is monitored. The remaining steps and parameters are the same as those of Example 1.

[0040] Comparative Example 1

[0041] This example was carried out according to the method of Example 1, except that in step (3), Spearman correlation analysis was not performed, and only the characteristic microbial community structure was monitored. The remaining steps and parameters were the same as in Example 1.

[0042] Test Example 1

[0043] The changes in the relative abundance of functional bacterial genera in Examples 1 to 3 are summarized as shown in Table 1.

[0044] Table 1

[0045]

[0046] It can be seen from the results in Table 1 that, compared with the reference benchmark, when the effluent TN of the sewage treatment plant in Example 1 does not meet the discharge standard, the fluctuation range of the relative abundance of its total denitrifying bacteria decreases; when the effluent TP of the sewage treatment plant in Example 2 does not meet the discharge standard, the fluctuation range of the relative abundance of its total polyphosphate-accumulating bacteria decreases; when the activated sludge of the sewage treatment plant in Example 3 is in a micro-expansion state, the fluctuation range of the relative abundance of its total EPS-secreting bacteria and filamentous bacteria increases significantly.

[0047] Test Example 2

[0048] The correlation analysis between environmental factors and abnormal bacterial genera in Examples 1 to 3 is summarized as shown in Table 2.

[0049] Table 2

[0050]

[0051] In Table 2, “*” indicates a significant correlation at P < 0.05.

[0052] As shown in Table 2, the relative abundance of Denitrifying Bacteria and the influent COD concentration in Example 1 meet the significant positive correlation conditions of a correlation coefficient of absolute value close to 1 and a P value of <0.05; the low influent COD concentration is not conducive to the survival of Denitrifying Bacteria. The Polyphosphate Bacteria in Example 2 is significantly negatively correlated with SRT, and SRT affects the composition of Polyphosphate Bacteria in the microbial community. The Filamentous Fungi in Example 3 is significantly negatively correlated with water temperature. When the Filamentous Fungi overgrow, this situation can be improved by regulating the water temperature.

[0053] Furthermore, significant differences were found in the correlations between environmental factors and functional bacterial genera within sewage treatment plants, providing a strong scientific basis for optimizing and remediating sewage treatment plant operations. Specifically, changes in the relative abundance of Denitrifying Bacteria, Polyphosphate-Accumulating Bacteria, and Filamentous Bacteria reflect issues within the sewage treatment process, and the manipulation of environmental factors can effectively influence the composition of microbial communities, thereby improving sewage treatment efficiency. These results demonstrate that dynamic monitoring and optimization based on functional bacterial genera and environmental factors is crucial for the efficient operation of sewage treatment plants and can provide scientific support for real-time regulation of sewage treatment plants.

[0054] In contrast, Comparative Example 1 in this example did not employ Spearman correlation analysis, but instead monitored only the microbial community structure. While this method can provide basic information on the composition of microbial communities, it lacks quantitative analysis and in-depth exploration of the interactions between microbial communities and environmental factors, resulting in an inability to fully identify environmental factors significantly associated with functional bacterial genera. This limitation makes regulatory decisions based solely on monitoring microbial community structure lack scientific basis and foresight, potentially leading to delayed responses to dynamic changes in microbial communities, thus impacting the optimization and stability of the wastewater treatment process.

[0055] This shows that monitoring methods that don't use Spearman correlation analysis are significantly inadequate in accurately identifying and regulating the relationship between environmental factors and microbial communities, resulting in insufficient assurance of the operational efficiency and stability of sewage treatment plants. In contrast, the present invention, through in-depth analysis of the coupling relationship between microbial communities and environmental factors, enables precise regulation of sewage treatment plants, significantly improving their operational efficiency.

[0056] The preferred embodiments of the present invention have been described in detail above, but the present invention is not limited thereto. Within the technical concept of the present invention, various simple variations of the technical solution of the present invention may be made, including combining the various technical features in any other appropriate manner. These simple variations and combinations should also be regarded as disclosed in the present invention and fall within the scope of protection of the present invention.

Claims

1. A method for coupling regulation of microbial communities and environmental factors in a sewage treatment plant, characterized in that: The method comprises the following steps: (1) Functional bacterial genera related to nitrogen and phosphorus pollutant removal and activated sludge settling performance in sewage treatment plants were selected as characteristic microbial communities; (2) When the sewage treatment plant meets the corresponding discharge standards, regularly collect activated sludge samples throughout the year to determine the relative abundance range of functional bacterial genera and form a reference benchmark; (3) When the operation of the sewage treatment plant becomes unstable, the characteristic microbial community structure described in step (1) is monitored, abnormal bacterial genera are screened out, and the correlation coefficient matrix between environmental factors and abnormal bacterial genera is calculated based on Spearman correlation analysis to identify environmental factors that are significantly correlated with the characteristic microbial community.

2. The method according to claim 1, characterized in that In step (1), the functional bacteria are nitrifying bacteria, denitrifying bacteria, phosphate accumulating bacteria, denitrifying phosphate accumulating bacteria, filamentous bacteria and EPS secreting bacteria.

3. The method according to claim 1, characterized in that In step (2), the frequency of regularly collecting activated sludge samples throughout the year is once a month.

4. The method according to claim 1, wherein In step (2), the relative abundance of functional bacterial genera was determined by using the screening condition of relative abundance > 0.01% in samples from at least one month to determine the variation range of the relative abundance of functional bacterial genera.

5. The method according to claim 1, wherein In step (3), the unstable operation of the sewage treatment plant includes: the effluent TN does not meet the discharge standard, the effluent TP does not meet the discharge standard, or the activated sludge is in a micro-expansion state.

6. The method according to claim 1, characterized in that In step (3), the abnormal bacterial genus is a bacterial genus that deviates from the relative abundance reference benchmark in step (2).

7. The method according to claim 1, characterized in that In step (3), the environmental factors are influent COD, influent TN, influent TP, DO, MLSS, MLVSS, ORP, pH, OUR, SRT or water temperature.

8. The method according to claim 1, characterized in that In step (3), identifying environmental factors significantly correlated with the microbial community is identifying environmental factors whose absolute value of the correlation coefficient with the characteristic microbial community in step (1) is close to 1 and whose P value is <0.05.

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