PH value adjusting method and system for soil remediation

Abstract

The invention provides a pH value adjusting method and system for soil remediation, and relates to the field of soil pollution remediation, the pH value and ORP value of soil are obtained and analyzed, the dominant mode of pH change is determined based on coupling judgment logic, then the remediation agent adding strategy is adjusted, and the remediation effect is improved. The problem that the influence of microbial activity on pH is not fully considered in the prior art is effectively solved, blind adding of a repairing agent is avoided, the repairing accuracy and efficiency are improved, the problems that in the prior art, the biogeochemical process is not effectively coupled, the reason of pH change is difficult to accurately recognize, and the repairing agent is too excessive or insufficient are solved, and the repairing effect is improved. And the repairing accuracy and sustainability are improved.

Description

Technical Field

[0001] The present invention relates to the field of soil pollution remediation, and in particular to a pH value adjustment method and system for soil remediation. Background Art

[0002] In the field of soil contamination remediation, regulating soil pH is a crucial means of controlling pollutant migration and transformation, enhancing microbial degradation activity, and promoting plant growth. Existing technologies often use feedback systems based on online pH monitoring to guide the addition of remediation agents (such as calcareous amendments). These systems typically deploy multiple pH sensors at multiple locations and depths throughout the contaminated area to collect real-time soil pH data. Control algorithms then calculate the dosage and timing of remediation agent addition. In actual remediation processes, it has been found that despite adhering to the instructions of existing pH feedback systems, soil pH in some areas can still experience unexpected fluctuations or even declines. This is particularly true in remediation projects focused on restoring the ecological functions of indigenous microorganisms. Existing feedback systems, which fail to recognize and respond to dynamic microbially mediated pH changes, severely impact the accuracy and sustainability of remediation efforts. Even if operators can identify microbial changes through microbial analysis, it can be difficult to effectively integrate these changes into automated control loops, hindering the coordinated regulation of soil pH through biological and chemical coupling.

[0003] In view of the above problems, the existing technology is in urgent need of improvement. Summary of the Invention

[0004] The present application discloses a pH adjustment method and system for soil remediation, which aims to solve the technical problems that existing soil pH adjustment methods fail to effectively couple the dynamic feedback of complex biogeochemical processes, resulting in inaccurate remediation agent addition strategies, increased remediation costs, and poor remediation effects.

[0005] In a first aspect, the present application discloses a method for adjusting pH value for soil remediation, the method comprising: Obtaining the pH value of at least one monitoring depth of the soil and its corresponding soil oxidation-reduction potential (ORP) value; Comparing the pH value of the at least one monitoring depth with the pH target range at the monitoring depth to obtain a comparison result; evaluating the state of the ORP value relative to the ORP reference range at the monitoring depth and its change trend to obtain an evaluation result; Based on the comparison results, the evaluation results, and the preset pH-ORP coupling judgment logic, the dominant mode of change of the soil pH value at the monitoring depth is determined; the dominant mode of change includes chemical action dominance and microbial metabolic activity dominance; According to the dominant mode of change, the remediation agent addition strategy for adjusting the soil pH value at the monitoring depth is adjusted to perform pH adjustment.

[0006] Furthermore, based on the comparison result, the evaluation result and the preset pH-ORP coupling judgment logic, the dominant mode of change of the soil pH value at the monitoring depth is determined, including: Based on the comparison result, the evaluation result and the preset pH-ORP coupling judgment logic, a preliminary judgment is made to obtain a preliminary judgment result; When the preliminary identification result indicates that there are multiple microbial metabolic activities that jointly affect the pH value, or indicates that there are multiple microbial metabolic activities that jointly act on the soil, resulting in changes in the pH value and the ORP value that are not in a preset pattern, the dominant bacterial community type in the soil at the monitoring depth is identified; Based on the identified dominant bacterial group type, adjusting the preset pH-ORP coupling judgment logic to obtain an adjusted pH-ORP coupling judgment logic; Based on the comparison results, the evaluation results and the adjusted pH-ORP coupling judgment logic, the dominant mode of change in the soil pH value at the monitoring depth is determined.

[0007] More specifically, in some embodiments, identifying the dominant bacterial group type in the soil at the monitoring depth comprises: Determining a microbial population in the soil at the monitoring depth whose number or biomass exceeds a preset threshold as a dominant microbial population, and obtaining identification information of the dominant microbial population; the identification information includes the type of the dominant microbial population and the known effect of the dominant microbial population on the pH value and ORP value of the soil; For each dominant microbial population, based on its known influence pattern on the pH value and ORP value of the soil, and in combination with the currently acquired direction of change of the pH value and the ORP value at the at least one monitoring depth, the contribution of the dominant microbial population to the current change of the pH value and the ORP value is evaluated; the direction of change of the pH value and the direction of change of the ORP value both include increasing, decreasing, and stable; According to the contribution degree, one or more dominant microbial populations that play a leading role in the current changes in the pH value and the ORP value are determined and determined as the identified dominant bacterial population type.

[0008] Preferably, evaluating the contribution of the dominant microbial population to the current changes in the pH value and the ORP value includes: Obtaining an initial contribution assessment of the current dominant microbial population to the current changes in the pH and ORP values ​​based on the known influence pattern of the current dominant microbial population on the pH and ORP values ​​of the soil, in combination with the currently acquired directions of change in the pH and ORP values ​​at the at least one monitoring depth; Acquire synergy information and / or antagonism information between the current dominant microbial population and one or more other dominant microbial populations; and determine the degree of contribution of the dominant microbial population to the current changes in the pH value and the ORP value based on the initial contribution assessment, the synergy information and / or the antagonism information.

[0009] In some preferred embodiments, determining the contribution of the dominant microbial population to the current changes in the pH value and the ORP value based on the synergistic effect information and / or antagonistic effect information comprises: Obtaining a first current value of one or more synergy indicators characterizing the strength of the synergy; determining a first contribution level based on the first current value and the initial contribution assessment; and using the first contribution level as the contribution level of the current dominant microbial population to the current changes in the pH value and the ORP value; And / or, obtaining a second current value of one or more antagonism indicators that characterize the strength of the antagonism; determining a second contribution degree based on the second current value and the initial contribution assessment; and using the second contribution degree as the contribution degree of the current dominant microbial population to the current changes in the pH value and the ORP value.

[0010] Further, obtaining a first current value of one or more synergistic effect indicators characterizing the synergistic effect strength includes: Obtaining initial values ​​of the one or more synergistic indicators in the soil at a current monitoring depth; Obtaining at least one interference reference value for the current monitoring depth, the interference reference value being used to characterize the known influence of the soil matrix properties on the synergy indicator value, or being used to characterize the known influence of other non-synergistic microbial activities in the soil on the synergy indicator value, or being used to characterize the known influence of abiotic factors on the synergy indicator value; Based on the obtained initial value and the obtained at least one interference reference value, the initial value is corrected to obtain a corrected value; and the obtained corrected value is used as the first current value of the one or more synergistic indicators that characterize the synergistic intensity.

[0011] As an option, the method further includes: Parameter measurements are performed for soil matrix characteristics, other non-synergistic microbial activities, and abiotic factors at the current monitoring depth; The at least one interference reference value is determined according to the parameter measurement result.

[0012] Through this technical solution, the present application provides a specific way to obtain interference reference values. By measuring soil environmental parameters, it provides data support for correcting synergistic indicators, thereby enhancing the practicality and feasibility of the method.

[0013] In one embodiment, the parameter measurement results include a first measurement result, a second measurement result, and a third measurement result; wherein the parameter measurements are performed for the soil matrix properties, other non-synergistic microbial activities, and the abiotic factors at the current monitoring depth, respectively, including: Based on the soil matrix characteristics, measuring a soil physical and chemical parameter having a preset physical / chemical interaction relationship with the synergistic indicator value at a current monitoring depth to obtain a first measurement result; For the other non-cooperative microbial activity, measuring a parameter characterizing the metabolic pathway activity / metabolite of the non-cooperative microorganism at the current monitoring depth to obtain a second measurement result; With respect to the abiotic factor, an environmental parameter having a preset influence on the stability of the synergy indicator is measured at the current monitoring depth to obtain a third measurement result.

[0014] Furthermore, based on the identified dominant bacterial group type, the preset pH-ORP coupling judgment logic is adjusted to obtain an adjusted pH-ORP coupling judgment logic, including: Obtain the identified set of dominant bacterial species and the contribution of each dominant microbial species; Based on the dominant bacterial group type set and the contribution degree, the comprehensive influence pattern of the microbial community in the soil at the monitoring depth on the pH value and the ORP value is determined; According to the comprehensive impact model, the corresponding logic adjustment rule is searched in the preset logic adjustment rule library; Based on the found logic adjustment rule, the preset pH-ORP coupling judgment logic is adjusted.

[0015] In a second aspect, the present application also discloses a pH adjustment system for soil remediation, which includes an acquisition module, a comparison and evaluation module, a judgment module, and an adjustment and feedback module; wherein: An acquisition module is used to obtain the pH value of at least one monitoring depth of the soil and its corresponding soil oxidation-reduction potential (ORP) value; a comparison and evaluation module, configured to compare the pH value at the at least one monitoring depth with the pH target range at the monitoring depth to obtain a comparison result; and to evaluate the state of the ORP value relative to the ORP reference range at the monitoring depth and its changing trend to obtain an evaluation result; A judgment module is used to determine the dominant mode of change of the soil pH value at the monitoring depth based on the comparison result, the evaluation result and the preset pH-ORP coupling judgment logic; the dominant mode of change includes chemical action dominance and microbial metabolic activity dominance; The adjustment and feedback module is used to adjust the repair agent addition strategy for adjusting the soil pH value at the monitoring depth according to the dominant mode of the change, so as to perform pH adjustment.

[0016] Beneficial effects: First, the present application can accurately distinguish between the chemically dominant factors and the microbially dominant factors of soil pH changes, thereby avoiding misjudgments caused by incomplete information in the prior art. When the pH change is caused by microbial activity, the system will not blindly increase the addition of remediation agents, but will be able to adjust the remediation agent addition strategy based on the pH change characteristics mediated by microorganisms. Secondly, this precise judgment and strategy adjustment effectively solves the problem of excessive use of remediation agents, significantly reduces remediation costs, and reduces secondary environmental risks that may be caused by excessive addition of remediation agents. Furthermore, the present application integrates the dynamic feedback of biogeochemical processes into the pH adjustment strategy to make the soil remediation process more intelligent and adaptive, especially in remediation projects with the important goal of restoring the ecological functions of indigenous microorganisms. The present application can better support the growth and reproduction of microorganisms, and improve the efficiency and long-term stability of bioremediation. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for use in the embodiments. It should be understood that the following drawings only illustrate certain embodiments of the present invention and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other relevant drawings can be obtained based on these drawings without paying any creative work.

[0018] Figure 1 This is a schematic flow chart of a pH adjustment method for soil remediation disclosed in an embodiment of the present invention; Figure 2 It is a structural schematic diagram of a pH value adjustment system for soil remediation disclosed in an embodiment of the present invention. DETAILED DESCRIPTION

[0019] Example embodiments will now be described more fully with reference to the accompanying drawings. However, example embodiments can be embodied in many forms and should not be construed as limited to the examples set forth herein; rather, these embodiments are provided so that this disclosure will be thorough and complete and will fully convey the concepts of the example embodiments to those skilled in the art.

[0020] It should be noted that the “plurality” mentioned in this article refers to two or more.

[0021] Traditional soil remediation pH feedback systems, designed to restore local microbial ecosystems and reduce pollutant concentrations, rely primarily on chemical buffering and reaction kinetics to guide the addition of remediation agents. This process presents a challenge: the introduction of remediation agents, while directly affecting the pH chemically, also impacts the local microbial community in multiple ways.

[0022] For example, consider soil remediation at a site contaminated by heavy metals and organic matter. The goal is to adjust the soil pH to a range conducive to the growth of target remediation microorganisms and their ability to fix heavy metals. To this end, a multi-depth online pH monitoring and feedback control system was deployed. Sensors collected pH data at different depths and calculated the dosage of a calcareous amendment based on a soil chemical buffering model and the kinetics of the remediation agent's reaction. Initially, the system added the amendment according to the chemical model, and the pH gradually increased. However, after initially reaching the target range and maintaining it for a period of time, the pH at some monitoring points began to fluctuate unexpectedly, even falling back into the acidic range, even though the system continued to direct the addition of amendment. System troubleshooting revealed no abnormalities in the sensor and remediation agent distribution. Further analysis revealed that the added amendment altered the soil microenvironment and affected the metabolic activity of local microorganisms. For example, certain acid-producing microorganisms became reactivated following the environmental changes, and the organic acids they produced caused a localized drop in pH. The current feedback system, based solely on the chemical model, interpreted this microbial-mediated pH drop as ineffective remediation agents and instructed continued addition of amendments.

[0023] When faced with the above problem, the first thing that came to mind in this embodiment was to improve the soil chemical buffer model so that it could more accurately predict the chemical reaction effect of the remediation agent. However, this approach still cannot solve the changes, hysteresis, and nonlinear effects of microbial activity on pH.

[0024] In this regard, this embodiment proposes a soil pollution remediation pH feedback method, such as Figure 1 As shown, the method of this embodiment includes: S101, obtaining a pH value of soil at at least one monitoring depth and its corresponding soil oxidation-reduction potential (ORP) value; S102, comparing the pH value of the at least one monitoring depth with the pH target range at the monitoring depth to obtain a comparison result; evaluating the state of the ORP value relative to the ORP reference range at the monitoring depth and its change trend to obtain an evaluation result; S103, based on the comparison result, the evaluation result, and the preset pH-ORP coupling judgment logic, determining the dominant mode of change of the soil pH value at the monitoring depth; the dominant mode of change includes chemical action dominance and microbial metabolic activity dominance; S104: According to the dominant mode of the change, the strategy for adding the repair agent for adjusting the soil pH value at the monitoring depth is adjusted to perform pH adjustment.

[0025] In the field of soil remediation, pH and redox potential (ORP) are two key physical and chemical parameters that together reflect the biogeochemical state of the soil microenvironment. pH is used to measure the acidity and alkalinity of the soil, which directly affects the solubility, mobility, and activity of microorganisms. ORP characterizes the intensity and direction of redox reactions in the soil and is closely related to the oxygen content, organic matter decomposition, changes in heavy metal valence, and microbial metabolic activity in the soil. The method proposed in this application aims to achieve precise control of soil pH adjustment through the coordinated analysis of these two parameters.

[0026] Specifically, soil remediation is usually carried out at a specific contaminated site, which may contain contaminated layers of different depths. Therefore, monitoring of soil parameters usually needs to be carried out at multiple monitoring depths. The pH target range refers to the ideal pH value interval set according to the remediation goal. For example, for heavy metal pollution, the pH value may need to be adjusted to neutral or weak alkaline to promote the fixation of heavy metals. The ORP reference range is an ORP value interval preset according to soil type, pollution characteristics and remediation goals, which is used to assess whether the soil redox state is suitable.

[0027] The pH-ORP coupling judgment logic is the core of this application. It presets a series of rules for correlating pH values, ORP values ​​and their changing trends to determine the main driving factors of soil pH changes. These driving factors are divided into chemical action-dominated and microbial metabolic activity-dominated. Chemical action-dominated usually refers to the direct acid-base neutralization, precipitation or dissolution reaction between the remediation agent and the soil components. Microbial metabolic activity-dominated refers to the indirect or direct impact of the microbial community in the soil on the soil pH through its life activities (such as organic acid production, nitrification, denitrification, sulfate reduction, etc.). The remediation agent addition strategy refers to a plan for adjusting the type, dosage, frequency and method of addition of the remediation agent according to the determined dominant mode of pH change.

[0028] The present application provides a pH adjustment method for soil remediation, and its specific implementation method can be described as follows. First, the method includes obtaining the pH value of at least one monitoring depth of the soil and its corresponding soil redox potential (ORP) value. In practical applications, this can be achieved by burying pH sensors and ORP sensors at preset monitoring points and depths in the soil. For example, sensors can be installed at different depths such as 0-30 cm, 30-60 cm, and 60-90 cm at multiple representative locations in the contaminated area. These sensors can collect data periodically, for example, once an hour or a day, and transmit the collected pH and ORP value data to a data processing unit. As a preferred embodiment, soil samples at different monitoring depths can also be taken out by manual sampling, and measured in the laboratory using a pH meter and an ORP meter to obtain the corresponding pH and ORP values.

[0029] Secondly, the method includes comparing the pH value at the at least one monitoring depth with the pH target range at that monitoring depth to obtain a comparison result; and evaluating the state of the ORP value relative to the ORP reference range at that monitoring depth and its changing trend to obtain an evaluation result. After obtaining the pH and ORP value data, the data processing unit can process these data. Specifically, for the pH value, the currently monitored pH value can be compared with a preset pH target range at that monitoring depth. For example, if the target range is 6.5-7.5 and the current pH value is 6.0, the comparison result can indicate that the pH value is low. For the ORP value, it can be compared with a preset ORP reference range to evaluate its current state as oxidizing, reducing, or neutral. At the same time, by analyzing historical ORP data, the changing trend of the ORP value can be calculated, such as whether it is increasing, decreasing, or remaining stable. These comparisons and evaluations can be automatically completed in the data processing unit using a preset algorithm, generating corresponding comparison results and evaluation results.

[0030] Furthermore, the method includes determining the dominant mode of change in soil pH at the monitoring depth based on the comparison results, the evaluation results, and a preset pH-ORP coupling judgment logic. The dominant mode of change includes chemical action or microbial metabolic activity. After obtaining the pH comparison results and ORP evaluation results, the system invokes the preset pH-ORP coupling judgment logic. This logic can be a decision tree model or rule base that contains a mapping between pH, ORP, and their changing trends, and the dominant mode of pH change. For example, if the pH is low and the ORP value continues to decrease, accompanied by the production of reducing gases such as hydrogen sulfide, this may indicate that microbial metabolic activity (such as sulfate-reducing bacteria) is driving the pH change. If the pH is low but the ORP value does not change significantly, and the pH value rises rapidly after the remediation agent is added, this may indicate that chemical action is dominant. By applying this logic, the system can intelligently determine whether chemical action or microbial metabolic activity is the primary driver of soil pH change at the current monitoring depth.

[0031] Finally, the method includes adjusting the repair agent addition strategy for adjusting the soil pH value at the monitoring depth according to the dominant mode of the change to perform pH adjustment. Once the dominant mode of pH change is determined, the system can optimize the repair agent addition strategy based on this information. For example, if it is judged that chemical action is dominant, the dosage and frequency of the repair agent can be calculated according to the traditional stoichiometric model. If it is judged that microbial metabolic activity is dominant, it may be necessary to adjust the type of repair agent, such as selecting a repair agent that has less impact on a specific microbial community, or adding microbial nutrients at the same time to promote the growth of beneficial microorganisms, thereby indirectly adjusting the pH value. In addition, the addition method can also be adjusted, such as by adding small amounts in batches to avoid causing severe disturbances to the microbial community. As a result, more targeted repair measures can be taken according to the actual biogeochemical state of the soil to achieve precise regulation of pH value.

[0032] The key to this embodiment is the introduction of a preset pH-ORP coupling judgment logic. This logic can comprehensively analyze the comparison results of the pH value and the evaluation results of the ORP value, so as to intelligently determine the dominant mode of change in the soil pH value at the current monitoring depth, that is, whether it is dominated by chemical action or microbial metabolic activity. For example, when the pH value deviates from the target range and the ORP value shows a significant reductive change or a specific trend, the system may judge that it is dominated by microbial metabolic activity, because the acid-producing or alkali-producing metabolic processes of many microorganisms are accompanied by changes in the redox state. On the contrary, if the pH value change is highly consistent with the chemical reaction kinetics of the remediation agent, and the ORP value change is not obvious or is in line with the expectations of a pure chemical reaction, it may be judged that it is dominated by chemical action. Once the dominant mode of pH change is determined, the system can adjust the remediation agent dosing strategy for regulating the soil pH value at the monitoring depth based on this judgment. For example, if it is judged that chemical action is dominant, then the chemical neutralization ability and diffusion efficiency of the remediation agent can be focused on. If it is determined that microbial metabolic activity is dominant, it may be necessary to consider adjusting the type of remediation agent to avoid inhibiting beneficial microorganisms, or supplementing microbial nutrients to promote the growth of the target microbial community, thereby indirectly or synergistically regulating the pH value through biological pathways. Therefore, the method of the present application can overcome the limitations of traditional methods that rely solely on chemical models, achieve bio-chemical synergistic regulation of soil pH value adjustment, significantly improve the accuracy, efficiency and sustainability of remediation, and avoid the problem of excessive use of remediation agents or insufficient remediation.

[0033] The present application further proposes that the steps of determining the dominant mode of change in soil pH at the monitoring depth include: Based on the comparison result, the evaluation result and the preset pH-ORP coupling judgment logic, a preliminary judgment is performed to obtain a preliminary judgment result; When the preliminary identification result indicates that there are multiple microbial metabolic activities that jointly affect the pH value, or indicates that there are multiple microbial metabolic activities that jointly act on the soil, resulting in changes in the pH value and the ORP value that are not in a preset pattern, identifying the dominant bacterial community type in the soil at the monitoring depth; Adjusting the preset pH-ORP coupling judgment logic based on the identified dominant bacterial flora type to obtain an adjusted pH-ORP coupling judgment logic; Based on the comparison result, the evaluation result and the adjusted pH-ORP coupling judgment logic, the dominant mode of change of the soil pH value at the monitoring depth is determined.

[0034] Initial identification involves an initial analysis of soil pH and ORP monitoring data using the pre-set, universal pH-ORP coupled judgment logic to quickly identify potential dominant factors contributing to pH variations. Specifically, when the initial identification indicates the presence of multiple microbial metabolic activities that collectively influence pH, or the presence of multiple microbial metabolic activities acting on the soil, resulting in unpredictable changes in pH and ORP, the system further identifies the dominant bacterial community types in the soil at that monitoring depth. This step aims to delve deeper into the biological roots of complex or unusual pH-ORP variation patterns and, by identifying specific dominant microbial populations, provide a precise biological basis for subsequent logic adjustments. Based on this identification of the dominant bacterial community types, the pre-set pH-ORP coupled judgment logic is adjusted to produce adjusted pH-ORP coupled judgment logic. This adjustment process enables the judgment logic to better adapt to the microbial activity characteristics of specific soil environments, improving accuracy and pertinence. Ultimately, based on the comparison results, evaluation results, and adjusted pH-ORP coupled judgment logic, the dominant mode of soil pH variation at that monitoring depth can be more accurately determined.

[0035] In some preferred embodiments, suppose that in soil at a certain monitoring depth, preliminary identification results indicate a continuous decrease in pH while ORP changes are insignificant. This pattern does not fully align with the typical chemical reactions or single microbial activity patterns in the pre-set pH-ORP coupled judgment logic. In this case, the system triggers the dominant bacterial community identification process. Through gene sequencing or metabolite analysis, the system identifies a significant presence of sulfur-reducing bacteria (SRB) as the dominant bacterial community in the soil. SRB are known to metabolize under anaerobic conditions to produce hydrogen sulfide, which in turn causes a decrease in pH. Based on this identification, the pre-set pH-ORP coupled judgment logic is adjusted, for example, by increasing the weighting of the relationship between SRB metabolites (such as hydrogen sulfide) and pH and ORP, or by introducing a new judgment branch specifically to address pH drops driven by SRB. This adjusted logic will more accurately identify the dominant mode of pH drop as microbial metabolic activity, further narrowing it down to SRB activity. Therefore, the remediation agent dosing strategy can more precisely inhibit the activity of sulfur-reducing bacteria or neutralize their metabolites, rather than blindly performing broad-spectrum pH adjustments, thereby achieving more efficient and economical soil remediation.

[0036] In some embodiments, when the preliminary identification results indicate that there are multiple microbial metabolic activities that jointly affect the pH value, or indicate that there are multiple microbial metabolic activities that jointly act on the soil, resulting in changes in the pH value and ORP value that are not in a preset pattern, it is necessary to identify the dominant bacterial community type in the soil at the monitoring depth. Specifically, identifying the dominant bacterial community type in the soil at the monitoring depth may include the following steps: Determining a microbial population in the soil at the monitoring depth whose number or biomass exceeds a preset threshold as a dominant microbial population, and obtaining identification information of the dominant microbial population; the identification information includes the type of the dominant microbial population and the known effect pattern of the dominant microbial population on the pH value and ORP value of the soil; Identifying dominant microbial populations can be achieved through a variety of biological detection methods. For example, high-throughput sequencing technologies (such as 16S rRNA gene sequencing or metagenomic sequencing) can be used to analyze the composition of soil microbial communities. Based on the relative abundance or absolute number of each microbial population in the sequencing results, microbial populations whose number or biomass exceeds a preset threshold can be screened. The preset threshold can be set based on empirical values, historical data, or specific remediation objectives. The identification information obtained for the dominant microbial population can specifically include the taxonomic information of the microbial population (such as genus and species name) and its known impact patterns on soil pH and ORP values ​​during metabolic processes. For example, certain microorganisms may cause a decrease in pH by producing acidic metabolites (such as lactic acid and acetic acid) or reduce ORP values ​​by reducing nitrates and sulfates. These known impact patterns can be derived from published literature, databases, or laboratory research data.

[0037] According to each of the dominant microbial populations, based on its known influence pattern on the pH value and ORP value of the soil, and in combination with the currently acquired direction of change of the pH value and the ORP value at the at least one monitoring depth, the contribution of the dominant microbial population to the current change of the pH value and the ORP value is evaluated; the direction of change of the pH value and the direction of change of the ORP value both include increasing, decreasing, and stable; Specifically, for each identified dominant microbial population, its known impact pattern on pH and ORP is compared with the actual direction of change (increase, decrease, or stability) in the currently monitored soil pH and ORP values. For example, if a dominant bacterial community is known to cause a decrease in pH and an increase in ORP, and current monitoring data shows a decrease in pH and an increase in ORP, it can be preliminarily determined that this community has a high contribution to the current changes. The degree of contribution can be assessed using qualitative or quantitative methods. For example, different weights or scores can be assigned based on factors such as the degree of match and the strength of the impact.

[0038] According to the contribution degree, one or more dominant microbial populations that play a leading role in the current changes in the pH value and the ORP value are determined as the identified dominant bacterial population type.

[0039] Thus, after assessing the contribution of all dominant microbial populations, one or more microbial populations that contribute most significantly to the current pH and ORP changes can be identified based on pre-set discrimination rules. For example, a contribution threshold can be set, and all microbial populations with contributions exceeding that threshold can be identified as the dominant bacterial population type. These identified dominant bacterial population types will be used to subsequently adjust the pH-ORP coupling judgment logic to more accurately guide the dosing strategy of the remediation agent.

[0040] The present application further proposes that the steps of evaluating the contribution of the dominant microbial population to the changes in the current pH value and the ORP value include: Obtaining, based on the current dominant microbial population, an initial contribution assessment of the current dominant microbial population to the current changes in the pH and ORP values, based on the known patterns of the dominant microbial population's effects on the pH and ORP values ​​of the soil, and in combination with the currently acquired directions of change in the pH and ORP values ​​at the at least one monitoring depth; Acquire synergistic effect information and / or antagonistic effect information between the current dominant microbial population and one or more other dominant microbial populations; and determine the contribution of the dominant microbial population to the current changes in the pH value and the ORP value based on the initial contribution assessment, the synergistic effect information and / or the antagonistic effect information.

[0041] Specifically, obtaining an initial assessment of the contribution of the currently dominant microbial population to the current changes in pH and ORP values ​​involves pre-establishing the typical impact pattern of a specific dominant microbial population on pH and ORP values ​​under specific soil environmental conditions based on its biological characteristics, such as metabolic pathways, enzyme activity, and product types. For example, some microorganisms may cause a decrease in pH by producing organic acids while simultaneously consuming oxygen, leading to a decrease in ORP; while others may increase pH through ammoniation or affect ORP through redox reactions. Combined with the actual direction of change in pH and ORP values ​​(increasing, decreasing, or stable) obtained at the current monitoring depth, a preliminary assessment of the potential contribution of the dominant microbial population to the current changes can be made. For example, if a known acid-producing microorganism is present and the current pH is decreasing, its contribution to the pH decrease can be preliminarily assessed.

[0042] Furthermore, obtaining the synergistic effect information and / or antagonistic effect information between the current dominant microbial population and one or more other dominant microbial populations refers to identifying and quantifying the interactions within the microbial community. Synergistic effect information may include, for example, the metabolites of one microorganism serving as substrates for another microorganism, or multiple microorganisms participating in a complex biogeochemical cycle together, thereby enhancing the impact on pH or ORP values. For example, anaerobic ammonia oxidizing bacteria and methanogens may have synergistic effects in the nitrogen cycle and the carbon cycle, jointly affecting the redox state of the soil. Antagonistic effect information may include, for example, one microorganism producing antibiotics that inhibit the growth of other microorganisms, or competing for limited nutrients, thereby weakening the effects of other microorganisms on pH or ORP values. For example, certain fungi may secrete substances that inhibit bacterial growth, thereby indirectly affecting the pH change process dominated by bacteria. These synergistic effect information and / or antagonistic effect information can be derived from existing microbiological databases, literature research, or obtained through experimental analysis.

[0043] Thus, determining the contribution of the dominant microbial population to the current changes in the pH value and the ORP value based on the initial contribution assessment, the synergistic effect information and / or antagonistic effect information means revising and optimizing the preliminary assessment results. For example, if the initial contribution assessment of a microorganism shows that it has a significant effect on the pH value, but at the same time there is a dominant bacterial group with a strong antagonistic effect with it, its actual contribution may be adjusted downward. Conversely, if there is a dominant bacterial group with a strong synergistic effect with it, its contribution may be adjusted upward. This correction makes the contribution assessment of a single dominant microbial population closer to the actual soil microecological environment.

[0044] This application further proposes a method for determining the contribution of dominant microbial populations to the changes in current pH and ORP values ​​based on synergy information and / or antagonism information. The specific implementation method includes: Obtaining a first current value of one or more synergistic effect indicators characterizing the strength of the synergistic effect; determining a first contribution degree based on the first current value and the initial contribution assessment; and using the first contribution degree as the contribution degree of the current dominant microbial population to the current changes in the pH value and the ORP value; And / or, obtaining a second current value of one or more antagonism indicators that characterize the strength of the antagonism; determining a second contribution degree based on the second current value and the initial contribution assessment; and using the second contribution degree as the contribution degree of the current dominant microbial population to the current changes in the pH value and the ORP value.

[0045] Specifically, synergistic indicators can be biomarkers or metabolites that indicate the mutual promotion effect between two or more microbial populations. For example, certain microorganisms secrete specific enzymes, cofactors or signal molecules when they coexist, which can accelerate or enhance each other's metabolic activities, thereby producing a synergistic effect on the pH value or ORP value of the soil. The first current value refers to the value obtained by quantitatively measuring these synergistic indicators at the current monitoring depth, such as the concentration of a specific metabolite, the activity level of a key enzyme, or the expression level of a specific gene. Similarly, antagonistic indicators are biomarkers or metabolites that indicate the mutual inhibition effect between microbial populations. For example, certain microorganisms produce antibiotics, organic acids or other inhibitory substances, thereby limiting the growth or metabolic activity of other microorganisms, thereby affecting the pH value or ORP value of the soil. The second current value refers to the value obtained by quantitatively measuring these antagonistic indicators at the current monitoring depth, such as the concentration of inhibitory compounds or the expression level of related genes. Initial contribution assessment refers to a preliminary judgment of the potential contribution of the dominant microbial population to the current change before considering synergy and / or antagonism, based on the known impact pattern of the dominant microbial population on pH and ORP values ​​and the direction of change of the current pH and ORP values. After obtaining the first current value or the second current value, the value is used to modify the initial contribution assessment. For example, if the first current value of the synergy indicator is high, it indicates that the actual contribution of the dominant microbial population may be higher than the initial assessment, and the first contribution level will be adjusted accordingly. Conversely, if the second current value of the antagonism indicator is high, it indicates that the actual contribution of the dominant microbial population may be suppressed, and the second contribution level will be adjusted accordingly. This adjustment can be achieved through a preset mathematical model, weighting factor or machine learning-based algorithm to accurately quantify the impact of synergy or antagonism on the actual contribution.

[0046] The solution of the present application solves the problem of difficulty in accurately assessing the contribution of a single dominant bacterial group to changes in soil pH and ORP values ​​in complex microbial communities by introducing quantitative measurements of synergy indicators and / or antagonism indicators and revising the initial contribution assessment of dominant microbial populations based on these values. Specifically, when the metabolic activities of multiple microorganisms jointly affect the pH value or cause changes in pH and ORP values ​​that are not in a preset pattern, the traditional preliminary assessment based on known impact patterns may not be able to fully capture the complex interactions between microorganisms. By obtaining current values ​​that characterize the strength of synergy or antagonism, the actual impact of these interactions can be more accurately reflected. For example, if there is synergy between two dominant bacterial groups, the value of their synergy indicator will be enhanced. By incorporating this value into the contribution assessment, the actual driving effect of their joint action on changes in pH and ORP values ​​can be more realistically reflected. Conversely, if there is antagonism, the value of the antagonism indicator will be suppressed. By incorporating it into the assessment, the contribution of a certain bacterial group can be avoided from being overestimated. This method can thus transform the dynamic complexity of microbial communities into quantifiable parameters, enabling a more refined and accurate assessment of the contributions of dominant microorganisms. This in turn provides a more reliable basis for subsequent adjustments to the pH-ORP coupling logic, ultimately enabling more precise and effective formulation of soil pH adjustment strategies, significantly improving the relevance and success rate of soil remediation efforts.

[0047] In some preferred embodiments, suppose that in the soil at a certain monitoring depth, a preliminary assessment indicates that Denitrifying Bacteria contributes primarily to the decrease in pH and increase in ORP. However, further analysis reveals the presence of Sulfur-Reducing Bacteria in the soil, and it is known that Denitrifying Bacteria and Sulfur-Reducing Bacteria interact synergistically, jointly promoting the degradation of organic matter and producing acidic substances. To more accurately assess the contribution of Denitrifying Bacteria, the present application obtains a first current value of one or more synergy indicators that characterize the strength of this synergy. For example, the concentration of specific organic acids (such as acetic acid and propionic acid) in the soil can be measured. These organic acids are products of the synergistic metabolism of two bacterial groups. If the first current value of these organic acids is high, indicating a greater synergistic effect, the initial contribution estimate of Denitrifying Bacteria will be adjusted upward, resulting in a higher first contribution. Conversely, if Nitrifying Bacteria are found in the soil, and it is known that Denitrifying Bacteria and Nitrifying Bacteria may interact antagonistically (e.g., competing for nitrogen sources), the present application obtains a second current value of one or more antagonism indicators that characterize the strength of this antagonism. For example, the concentration of nitrite or nitrate in the soil, which are products of nitrifying bacteria metabolism, can be measured. If these secondary current values ​​are high, indicating a strong antagonistic effect, the initial contribution estimate of "Denitrifying Bacteria" may be adjusted downward, resulting in a lower secondary contribution. In this way, the actual contribution of "Denitrifying Bacteria" in the current soil environment can be more accurately determined, providing more refined guidance for subsequent remediation agent dosing strategies.

[0048] The present application further proposes a method for obtaining a first current value of one or more synergistic effect indicators representing the synergistic effect strength, the steps of which include: obtaining initial quantity values ​​of the one or more synergistic indicators in the soil at a current monitoring depth; Obtaining at least one interference reference value for the current monitoring depth, the interference reference value being used to characterize the known influence of the soil matrix properties on the synergy indicator value, or being used to characterize the known influence of other non-synergistic microbial activities in the soil on the synergy indicator value, or being used to characterize the known influence of abiotic factors on the synergy indicator value; Based on the obtained initial value and the obtained at least one interference reference value, the initial value is corrected to obtain a corrected value; and the obtained corrected value is used as the first current value of the one or more synergistic indicators that characterize the synergistic intensity.

[0049] Specifically, obtaining the initial values ​​of one or more synergistic indicators refers to directly measuring or detecting the current values ​​of specific substances or parameters in the soil related to microbial synergy through conventional soil analysis methods, such as chemical analysis and biological testing. These indicators can be microbial metabolites, enzyme activity, specific gene expression levels, etc., and their values ​​should ideally directly reflect the strength of the synergistic effect.

[0050] Obtaining at least one interference reference value is crucial to this approach. This interference reference value can be understood as a quantification of factors that have non-synergistic effects on the synergistic indicator value. These factors include, but are not limited to, the physicochemical properties of the soil (such as soil texture, organic matter content, and ionic strength), the activity of other non-synergistic microbial communities present in the soil (for example, some microorganisms may produce substances similar to synergistic indicators, but their effects are not synergistic), and the impact of abiotic environmental factors (such as temperature, humidity, light, and pollutant concentrations) on indicator stability and detection accuracy. These interference reference values ​​can be obtained through pre-established models, historical data, or real-time measurements.

[0051] In practical applications, correcting the initial value based on the obtained initial value and at least one obtained interference reference value refers to removing deviations from the initial value caused by interference factors through a mathematical model or algorithm, thereby obtaining a corrected value that is closer to the true synergistic effect strength. For example, correction can be performed using linear regression, multivariate analysis, or an algorithm based on a specific correction coefficient. The corrected value is considered the first current value representing the synergistic effect strength and is used in subsequent contribution assessments.

[0052] This application further proposes a method for determining an interference reference value, the method further comprising: Parameter measurements are performed for soil matrix characteristics, other non-synergistic microbial activities, and abiotic factors at the current monitoring depth; The at least one interference reference value is determined according to the parameter measurement result.

[0053] Specifically, based on the soil matrix characteristics at the current monitoring depth, soil physicochemical parameters with pre-defined physical / chemical interactions with the synergistic indicator value can be measured. For example, if the synergistic indicator is an ion, the soil's cation exchange capacity (CEC), clay mineral content, and organic matter content can be measured. These parameters can affect the adsorption, desorption, or migration of ions, thereby affecting their actual value in the soil.

[0054] For other non-synergistic microbial activities, parameters characterizing the metabolic pathway activity or metabolites of these non-synergistic microorganisms can be measured. For example, if the synergistic indicator is a metabolic intermediate, and other non-synergistic microorganisms in the soil can also produce or consume this intermediate, the specific enzyme activity or concentration of their characteristic metabolites can be measured to quantify their impact on the synergistic indicator.

[0055] For abiotic factors, environmental parameters with a pre-defined influence on the stability of the synergy indicator can be measured. For example, if the synergy indicator is susceptible to degradation at a specific temperature, soil temperature can be measured; if it is unstable under specific redox conditions, soil redox potential (ORP) or dissolved oxygen content can be measured. Measuring these environmental parameters can help assess the direct influence of abiotic factors on the synergy indicator value.

[0056] The solution of the present application can comprehensively and quantitatively obtain information on various potential interference factors that affect the value of the synergy indicator by measuring parameters of the soil matrix characteristics, other non-synergistic microbial activities and abiotic factors at the current monitoring depth. Thus, based on the results of these parameter measurements, the at least one interference reference value can be accurately determined based on a preset physicochemical model, biogeochemical model or empirical relationship. This method ensures that the acquisition of the interference reference value is based on actual soil environmental conditions and complex biogeochemical processes, thereby making the subsequent correction of the initial value of the synergy indicator more accurate and reliable.

[0057] In some preferred embodiments, a specific example is provided below. Suppose, during a soil remediation process, the synergistic effect of a particular acid-producing microorganism (e.g., Thiobacillus) needs to be assessed, and the synergistic indicator is sulfate ion concentration. However, various factors in the soil may affect the actual sulfate ion concentration. Specifically, soil matrix properties at the current monitoring depth can be measured, such as clay content and organic matter content. For example, clay minerals may adsorb sulfate ions, and the decomposition of organic matter may also affect sulfate concentration. To assess other non-synergistic microbial activity, the activity of sulfate-reducing bacteria (SRB) in the soil or the abundance of their characteristic genes can be measured. SRB reduce sulfate to sulfide, thereby reducing sulfate concentration, which is a non-synergistic interference. Abiotic factors can be measured, such as soil temperature and moisture content. For example, high temperatures may accelerate sulfate biodegradation or chemical transformation, while moisture content affects ion mobility and solubility. After obtaining these parameter measurements, a reference interference value can be determined based on a pre-set model or empirical data. For example, based on the measured clay content, the average amount of sulfate adsorbed by the clay under current conditions can be accessed or calculated as a reference value for interference caused by soil matrix properties. Based on the SRB activity measurement results, the SRB consumption rate under current conditions can be estimated as a reference value for interference caused by other non-synergistic microbial activities. Based on the soil temperature and moisture content, the abiotic degradation or conversion rate of sulfate can be estimated as a reference value for interference caused by abiotic factors. These determined interference reference values ​​are then used to correct the actual measured initial sulfate ion value, thereby obtaining a more accurate first current value that characterizes the strength of the synergistic effect of Thiobacillus.

[0058] Specifically, the above parameter measurement results may include a first measurement result, a second measurement result, and a third measurement result.

[0059] Among them, parameters are measured for soil matrix characteristics, other non-synergistic microbial activities, and abiotic factors at the current monitoring depth, including: Based on the soil matrix characteristics, measuring a soil physical and chemical parameter having a preset physical / chemical interaction relationship with the synergistic indicator value at a current monitoring depth to obtain a first measurement result; For the other non-cooperative microbial activities, measuring parameters characterizing metabolic pathway activities / metabolites of the non-cooperative microorganisms at the current monitoring depth to obtain a second measurement result; With respect to the abiotic factors, an environmental parameter having a preset influence on the stability of the synergy indicator is measured at a current monitoring depth to obtain a third measurement result.

[0060] Specifically, the first measurement result refers to data obtained from measuring soil physicochemical parameters at the current monitoring depth that have a pre-determined physical / chemical relationship with the synergistic indicator value. These parameters may include, but are not limited to, soil texture (e.g., the proportion of sand, loam, and clay), organic matter content, cation exchange capacity (CEC), soil moisture content, and soil density. For example, certain synergistic indicators may exhibit different activity or stability under specific soil textures or organic matter contents. By measuring these physicochemical parameters, the influence of the soil matrix on the synergistic indicator can be quantified.

[0061] Secondary measurements refer to data obtained by measuring parameters characterizing the metabolic pathway activity or metabolites of other non-synergistic microorganisms at the current monitoring depth. These parameters are intended to reflect the activity level of non-synergistic microbial communities in the soil and their potential interference with synergy indicators. For example, enzyme activities (e.g., nitrification and denitrification) or concentrations of specific metabolites (e.g., volatile fatty acids and sulfides) of specific non-synergistic microbial populations can be measured, or the abundance or expression levels of specific non-synergistic microbial genes can be quantified using molecular biology methods (e.g., qPCR). These measurements help identify and quantify the consumption, conversion, or inhibition of synergy indicators by non-synergistic microorganisms.

[0062] The third measurement result refers to data obtained from measuring environmental parameters at the current monitoring depth that have a pre-determined impact on the stability of the synergy indicator. These parameters are typically abiotic factors in the soil environment that may directly affect the physicochemical properties or biological activity of the synergy indicator. Examples include soil temperature, oxidation-reduction potential (ORP), dissolved oxygen concentration, heavy metal ion concentration, salinity, or light intensity. Changes in these environmental parameters may lead to degradation, inactivation, or morphological changes of the synergy indicator, thus affecting the accuracy of its measurement.

[0063] The solution of the present application performs detailed parameter measurements on soil matrix properties, other non-synergistic microbial activities, and abiotic factors, and obtains the first measurement result, the second measurement result, and the third measurement result, which can more comprehensively and accurately identify and quantify the various interfering factors that affect the value of the synergy indicator. As a result, reliable reference data can be provided for the subsequent correction of the initial value of the synergy indicator to ensure that the corrected value can more truly reflect the actual intensity of the synergy. This refined measurement and correction mechanism makes the assessment of the synergy between dominant bacterial types more accurate, and thus provides a solid data foundation for adjusting the pH-ORP coupling judgment logic.

[0064] Specifically, adjusting the preset pH-ORP coupling judgment logic based on the identified dominant bacterial group type to obtain the adjusted pH-ORP coupling judgment logic may include the following steps: Obtain the set of identified dominant bacterial species and the contribution assessed for each dominant microbial population; Determine, based on the set of dominant bacterial community types and the degree of contribution, a comprehensive influence pattern of the microbial community in the soil at the monitoring depth on the pH value and the ORP value; According to the comprehensive impact model, searching for corresponding logic adjustment rules in a preset logic adjustment rule library; Based on the found logic adjustment rule, the preset pH-ORP coupling judgment logic is adjusted.

[0065] Among them, obtaining the identified set of dominant bacterial group types refers to identifying the microbial populations that dominate in terms of quantity or biomass during the soil remediation process through microbial community analysis technologies, such as high-throughput sequencing and qPCR. The types of these dominant microbial populations and their known impact patterns on soil pH and ORP values ​​will be recorded. For each identified dominant microbial population, it is necessary to evaluate its specific contribution to the current changes in soil pH and ORP values. This can be accomplished by analyzing its metabolic pathways, products, and interactions with other microorganisms.

[0066] Furthermore, based on the set of dominant bacterial species and their contributions, a comprehensive model of the impact of the microbial community on the pH and ORP values ​​in the soil at the monitoring depth is determined. This means integrating all identified dominant microbial populations and their respective contributions to form a comprehensive model that reflects the impact of the entire microbial community on pH and ORP values. This comprehensive impact model can be a mathematical model, a logical decision tree, or a set of rules based on expert knowledge, which describes how different microbial activities jointly drive changes in pH and ORP values ​​in a specific soil environment.

[0067] Furthermore, based on the comprehensive impact pattern, a corresponding logic adjustment rule is searched in a preset logic adjustment rule library. The logic adjustment rule library is a pre-established knowledge base that contains pH-ORP coupling judgment logic adjustment schemes for different microbial comprehensive impact patterns. For example, if the comprehensive impact pattern shows that the activity of a certain acid-producing bacterial group increases under specific ORP conditions, there may be a rule in the rule library indicating that the pH-ORP coupling judgment logic should be adjusted in similar situations to make it more inclined to consider the impact of microbial acid production.

[0068] Finally, based on the found logic adjustment rules, the preset pH-ORP coupling judgment logic is adjusted. This means applying specific adjustment rules retrieved from the rule library to the current pH-ORP coupling judgment logic, enabling it to more accurately reflect the impact of the complex microbial metabolic activities in the current soil on pH and ORP values. This adjustment can include modifying judgment thresholds, changing judgment priorities, or introducing new judgment conditions.

[0069] The solution of the present application can more accurately grasp the impact of microbial metabolic activities on changes in soil pH by deeply analyzing the types of dominant bacterial communities in the soil and the degree of their contribution to pH and ORP values. When the preliminary judgment results indicate that there are multiple microbial metabolic activities that jointly affect the pH value, or cause the pH and ORP values ​​to change in non-preset patterns, the traditional pH-ORP coupling judgment logic may not be able to accurately identify the dominant mode of pH change. By identifying the types of dominant bacterial communities and evaluating their contributions, a comprehensive impact model of microbial communities that is more in line with actual conditions can be constructed. Based on this comprehensive impact model, the corresponding adjustment rules are searched and applied from the preset logic adjustment rule library, so that the pH-ORP coupling judgment logic can dynamically adapt to the complex microbial environment, thereby avoiding the problem of improper repair agent addition strategy caused by misjudging the dominant mode of pH change. As a result, the present application can effectively improve the accuracy and efficiency of soil pH adjustment.

[0070] In addition, this application proposes a pH adjustment system for soil remediation, such as Figure 2 As shown, the system includes an acquisition module 201, a comparison and evaluation module 202, a judgment module 203, and an adjustment and feedback module 204; wherein: An acquisition module 201 is configured to acquire a pH value of soil at at least one monitoring depth and its corresponding soil oxidation-reduction potential (ORP) value; The comparison and evaluation module 202 is configured to compare the pH value at the at least one monitoring depth with the pH target range at the monitoring depth to obtain a comparison result; evaluate the state of the ORP value relative to the ORP reference range at the monitoring depth and its change trend to obtain an evaluation result; The judgment module 203 is used to determine the dominant mode of change of the soil pH value at the monitoring depth based on the comparison result, the evaluation result and the preset pH-ORP coupling judgment logic; the dominant mode of change includes chemical action dominance and microbial metabolic activity dominance; The adjustment and feedback module 204 is used to adjust the repair agent addition strategy for adjusting the soil pH value at the monitoring depth according to the dominant mode of change, so as to perform pH adjustment.

[0071] The specific implementation methods described above further illustrate the objectives, technical solutions and beneficial effects of the present invention in detail. It should be understood that the above description is only a specific implementation method of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A method for adjusting pH value for soil remediation, characterized in that: The method comprises: Obtaining the pH value of at least one monitoring depth of the soil and its corresponding soil oxidation-reduction potential (ORP) value; Comparing the pH value of the at least one monitoring depth with the pH target range at the monitoring depth to obtain a comparison result; evaluating the state of the ORP value relative to the ORP reference range at the monitoring depth and its change trend to obtain an evaluation result; Based on the comparison results, the evaluation results, and the preset pH-ORP coupling judgment logic, determining the dominant mode of change of the soil pH value at the monitoring depth; the dominant mode of change includes chemical action dominance and microbial metabolic activity dominance; According to the dominant mode of change, the remediation agent addition strategy for adjusting the soil pH value at the monitoring depth is adjusted to perform pH adjustment.

2. The pH adjustment method for soil remediation according to claim 1, characterized in that: The determining of the dominant mode of change of the soil pH value at the monitoring depth based on the comparison result, the evaluation result and the preset pH-ORP coupling judgment logic includes: Based on the comparison result, the evaluation result and the preset pH-ORP coupling judgment logic, a preliminary judgment is performed to obtain a preliminary judgment result; When the preliminary identification result indicates that there are multiple microbial metabolic activities that jointly affect the pH value, or indicates that there are multiple microbial metabolic activities that jointly act on the soil, resulting in changes in the pH value and the ORP value that are not in a preset pattern, identifying the dominant bacterial community type in the soil at the monitoring depth; Adjusting the preset pH-ORP coupling judgment logic based on the identified dominant bacterial flora type to obtain an adjusted pH-ORP coupling judgment logic; Based on the comparison result, the evaluation result and the adjusted pH-ORP coupling judgment logic, the dominant mode of change of the soil pH value at the monitoring depth is determined.

3. The pH adjustment method for soil remediation according to claim 2, characterized in that: Identify the dominant bacterial species in the soil at the monitoring depth, including: Determining a microbial population in the soil at the monitoring depth whose number or biomass exceeds a preset threshold as a dominant microbial population, and obtaining identification information of the dominant microbial population; the identification information includes the type of the dominant microbial population and the known effect pattern of the dominant microbial population on the pH value and ORP value of the soil; According to each of the dominant microbial populations, based on its known influence pattern on the pH value and ORP value of the soil, and in combination with the currently acquired direction of change of the pH value and the ORP value at the at least one monitoring depth, the contribution of the dominant microbial population to the current change of the pH value and the ORP value is evaluated; the direction of change of the pH value and the direction of change of the ORP value both include increasing, decreasing, and stable; According to the contribution degree, one or more dominant microbial populations that play a leading role in the current changes in the pH value and the ORP value are determined as the identified dominant bacterial population type.

4. The pH adjustment method for soil remediation according to claim 3, characterized in that: Evaluate the contribution of the dominant microbial population to the changes in the current pH value and the ORP value, including: Obtaining, based on the current dominant microbial population, an initial contribution assessment of the current dominant microbial population to the current changes in the pH and ORP values ​​of the soil, based on the known patterns of the dominant microbial population's effects on the pH and ORP values ​​of the soil, and in combination with the currently acquired directions of change in the pH and ORP values ​​at the at least one monitoring depth; Acquire synergistic effect information and / or antagonistic effect information between the current dominant microbial population and one or more other dominant microbial populations; and determine the contribution of the dominant microbial population to the current changes in the pH value and the ORP value based on the initial contribution assessment, the synergistic effect information and / or the antagonistic effect information.

5. The pH adjustment method for soil remediation according to claim 4, characterized in that: Determining the contribution of the dominant microbial population to the current changes in the pH value and the ORP value based on the synergistic effect information and / or antagonistic effect information includes: Obtaining a first current value of one or more synergy indicators representing the strength of the synergy; determining a first contribution degree based on the first current value and the initial contribution assessment; and using the first contribution degree as the contribution degree of the current dominant microbial population to the current changes in the pH value and the ORP value; And / or, obtaining a second current value of one or more antagonism indicators that characterize the strength of the antagonism; determining a second contribution degree based on the second current value and the initial contribution assessment; and using the second contribution degree as the contribution degree of the current dominant microbial population to the current changes in the pH value and the ORP value.

6. The pH adjustment method for soil remediation according to claim 5, characterized in that: Obtaining a first current value of one or more synergistic effect indicators representing the synergistic effect strength comprises: obtaining initial quantity values ​​of the one or more synergistic indicators in the soil at a current monitoring depth; Obtaining at least one interference reference value for the current monitoring depth, the interference reference value being used to characterize the known influence of soil matrix properties on the synergy indicator value, or being used to characterize the known influence of other non-synergistic microbial activities in the soil on the synergy indicator value, or being used to characterize the known influence of abiotic factors on the synergy indicator value; Based on the obtained initial value and the obtained at least one interference reference value, the initial value is corrected to obtain a corrected value; and the obtained corrected value is used as the first current value of the one or more synergistic indicators that characterize the synergistic intensity.

7. The pH adjustment method for soil remediation according to claim 5, characterized in that: The method further comprises: Parameter measurements are performed for soil matrix characteristics, other non-synergistic microbial activities, and abiotic factors at the current monitoring depth; At least one interference reference value is determined according to the parameter measurement result.

8. The pH adjustment method for soil remediation according to claim 7, characterized in that: The parameter measurement results include a first measurement result, a second measurement result, and a third measurement result; The parameters of the soil matrix properties, other non-synergistic microbial activities, and the abiotic factors at the current monitoring depth are measured separately, including: Based on the soil matrix characteristics, measuring a soil physical and chemical parameter having a preset physical / chemical interaction relationship with the synergistic indicator value at a current monitoring depth to obtain a first measurement result; For the other non-cooperative microbial activities, measuring parameters characterizing metabolic pathway activities / metabolites of the non-cooperative microorganisms at the current monitoring depth to obtain a second measurement result; With respect to the abiotic factors, an environmental parameter having a preset influence on the stability of the synergy indicator is measured at a current monitoring depth to obtain a third measurement result.

9. The pH adjustment method for soil remediation according to claim 2, characterized in that: The step of adjusting the preset pH-ORP coupling judgment logic based on the identified dominant bacterial group type to obtain the adjusted pH-ORP coupling judgment logic includes: Obtain the set of identified dominant bacterial species and the contribution assessed for each dominant microbial population; Determine, based on the set of dominant bacterial community types and the degree of contribution, a comprehensive influence pattern of the microbial community in the soil at the monitoring depth on the pH value and the ORP value; According to the comprehensive impact model, searching for corresponding logic adjustment rules in a preset logic adjustment rule library; Based on the found logic adjustment rule, the preset pH-ORP coupling judgment logic is adjusted.

10. A pH adjustment system for soil remediation, characterized in that: The system includes an acquisition module, a comparison and evaluation module, a judgment module, and an adjustment and feedback module; wherein: An acquisition module is used to obtain the pH value of at least one monitoring depth of the soil and its corresponding soil oxidation-reduction potential (ORP) value; a comparison and evaluation module, configured to compare the pH value of the at least one monitoring depth with the pH target range at the monitoring depth to obtain a comparison result; and to evaluate the state of the ORP value relative to the ORP reference range at the monitoring depth and its change trend to obtain an evaluation result; A judgment module is used to determine the dominant mode of change of the soil pH value at the monitoring depth based on the comparison result, the evaluation result and the preset pH-ORP coupling judgment logic; the dominant mode of change includes chemical action dominance and microbial metabolic activity dominance; The adjustment and feedback module is used to adjust the repair agent addition strategy for adjusting the soil pH value at the monitoring depth according to the dominant mode of change, so as to perform pH adjustment.

Images