A method and system for pH adjustment in soil remediation

Abstract

This invention provides a method and system for adjusting pH values ​​in soil remediation, relating to the field of soil pollution remediation. By acquiring and analyzing soil pH and ORP values, and determining the dominant mode of pH change based on coupled judgment logic, the remediation agent addition strategy is adjusted accordingly. This effectively solves the problem that existing technologies fail to fully consider the impact of microbial activity on pH, avoids the blind addition of remediation agents, and improves the accuracy and efficiency of remediation. It has the advantages of solving the problems of existing technologies failing to effectively couple biogeochemical processes, making it difficult to accurately identify the causes of pH changes, and potentially leading to excessive or insufficient remediation agents, thus improving the accuracy and sustainability of remediation.

Description

Technical Field

[0001] This invention relates to the field of soil pollution remediation, and more specifically, to a method and system for adjusting pH value in soil remediation. Background Technology

[0002] In the field of soil pollution remediation, regulating soil pH is a crucial means of controlling pollutant migration and transformation, enhancing microbial degradation activity, and promoting plant growth. Current technologies often employ feedback systems based on online pH monitoring to guide the addition of remediation agents (such as lime-based amendments). These systems typically deploy multiple pH sensors at various depths and locations within the contaminated area to collect soil pH data in real time and calculate the dosage and timing of remediation agent addition using control algorithms. However, in actual remediation processes, it has been found that even when remediation agents are added according to the instructions of existing pH feedback systems, soil pH in some areas still exhibits unexpected fluctuations or even declines. Particularly in remediation projects where the restoration of indigenous microbial ecological functions is a key objective, existing feedback systems, unable to identify and respond to microbially mediated pH dynamics, severely impact the accuracy and sustainability of the remediation efforts. Even when operators understand microbial changes through microbial analysis, it is difficult to effectively integrate this information into automated control loops, hindering the synergistic regulation of soil pH under biochemical coupling.

[0003] To address the aforementioned issues, existing technologies urgently need improvement. Summary of the Invention

[0004] This application discloses a method and system for adjusting pH value in soil remediation, aiming 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 application strategies, increased remediation costs, and poor remediation effects.

[0005] In a first aspect, this application discloses a pH adjustment method for soil remediation, the method comprising:

[0006] Obtain the pH value and the corresponding soil redox potential (ORP) value at at least one monitoring depth in the soil;

[0007] Compare the pH value at at least one monitoring depth with the target pH range at that monitoring depth to obtain the comparison result; evaluate the status and trend of the ORP value relative to the ORP reference range at that monitoring depth to obtain the evaluation result.

[0008] Based on the comparison results, evaluation results, and the pre-set pH-ORP coupling judgment logic, the dominant mode of change in soil pH at this monitoring depth was determined; the dominant mode of change includes chemical action and microbial metabolic activity.

[0009] Based on the dominant mode of change, the remediation agent application strategy for soil pH adjustment at this monitoring depth was adjusted to perform pH adjustment.

[0010] Furthermore, based on the comparison results, evaluation results, and the pre-defined pH-ORP coupling judgment logic, the dominant mode of soil pH change at this monitoring depth is determined, including:

[0011] Based on the comparison results, evaluation results, and the preset pH-ORP coupling judgment logic, a preliminary judgment is made to obtain the preliminary judgment result;

[0012] When the preliminary judgment result indicates that multiple microbial metabolic activities jointly affect the pH value, or indicates that multiple microbial metabolic activities jointly act on the soil, causing the pH value and the ORP value to change in a non-preset pattern, the dominant bacterial community type in the soil at the monitoring depth is identified.

[0013] Based on the identified dominant bacterial group type, the preset pH-ORP coupling judgment logic is adjusted to obtain the adjusted pH-ORP coupling judgment logic.

[0014] Based on the comparison results, evaluation results, and the adjusted pH-ORP coupling judgment logic, the dominant mode of soil pH change at this monitoring depth was determined.

[0015] More specifically, in some implementation schemes, the dominant microbial community types in the soil at this monitoring depth are identified, including:

[0016] The dominant microbial populations in the soil at the monitoring depth that exceed a preset threshold in terms of quantity or biomass are identified as the dominant microbial populations, and the identification information of the dominant microbial populations is obtained. The identification information includes the type of the dominant microbial population and the known influence patterns of the dominant microbial populations on the pH and ORP values ​​of the soil.

[0017] Based on each dominant microbial population, and considering its known influence patterns on the soil's pH and ORP values, combined with the current pH and ORP change directions at at least one monitoring depth, the contribution of the dominant microbial population to the current pH and ORP changes is assessed; the pH and ORP change directions include increasing, decreasing, and stable.

[0018] Based on the degree of contribution, one or more dominant microbial populations that play a leading role in the current changes in pH and ORP are identified as the dominant bacterial population types.

[0019] Preferably, assessing the contribution of the dominant microbial population to the current changes in pH and ORP includes:

[0020] Based on the current dominant microbial population, and considering its known influence patterns on the pH and ORP values ​​of the soil, combined with the current direction of pH and ORP changes at at least one monitoring depth, an initial assessment of the contribution of the current dominant microbial population to the current changes in pH and ORP values ​​is obtained.

[0021] Obtain information on the synergistic and / or antagonistic effects 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 pH and ORP changes based on the initial contribution assessment and the synergistic and / or antagonistic effect information.

[0022] In some preferred embodiments, the contribution of the dominant microbial population to the current pH and ORP changes is determined based on the synergistic and / or antagonistic information, including:

[0023] Obtain a first current value of one or more synergistic indicators characterizing the strength of the synergistic effect; determine a first degree of contribution based on the first current value and the initial contribution assessment; and use the first degree of contribution as the degree of contribution of the current dominant microbial population to the current changes in the pH and ORP values.

[0024] And / or, obtain a second current value of one or more antagonistic indicators characterizing the strength of the antagonistic effect; determine a second degree of contribution based on the second current value and the initial contribution assessment; and use the second degree of contribution as the degree of contribution of the current dominant microbial population to the current changes in the pH and ORP values.

[0025] Further, obtaining a first current value for one or more synergy indicators characterizing the strength of the synergy includes:

[0026] Obtain the initial values ​​of one or more synergistic indicators in the soil at the current monitoring depth;

[0027] For the current monitoring depth, at least one interference reference value is obtained. This interference reference value is used to characterize the known influence of the soil matrix characteristics on the synergistic indicator value, or to characterize the known influence of other non-synergistic microbial activities in the soil on the synergistic indicator value, or to characterize the known influence of abiotic factors on the synergistic indicator value.

[0028] Based on the acquired initial value and the acquired at least one interference reference value, the initial value is corrected to obtain a corrected value; the obtained corrected value is used as the first current value of the one or more synergy indicators characterizing the strength of the synergy.

[0029] As an optional approach, the method also includes:

[0030] Parameters were measured for soil matrix characteristics, other non-synergistic microbial activities, and abiotic factors at the current monitoring depth.

[0031] Based on the parameter measurement results, determine the value of at least one interference reference quantity.

[0032] This application provides a specific way to obtain interference reference values ​​through this technical solution. By measuring soil environmental parameters, it provides data support for calibrating synergistic indicators, thereby enhancing the practicality and feasibility of the method.

[0033] In one embodiment, the parameter measurement results include a first measurement result, a second measurement result, and a third measurement result; wherein, parameter measurements are performed for the soil matrix characteristics, other non-synergistic microbial activities, and the abiotic factors at the current monitoring depth, including:

[0034] Based on the characteristics of this soil matrix, the soil physicochemical parameters that have a preset physical / chemical relationship with the amount of the synergistic indicator are measured at the current monitoring depth to obtain the first measurement result;

[0035] For other non-synergistic microbial activities, parameters characterizing the metabolic pathway activity / metabolites of the non-synergistic microorganism are measured at the current monitoring depth to obtain a second measurement result;

[0036] To address this abiotic factor, environmental parameters that have a predetermined impact on the stability of the synergistic indicator are measured at the current monitoring depth to obtain a third measurement result.

[0037] Furthermore, based on the identified dominant bacterial group type, the preset pH-ORP coupling judgment logic is adjusted to obtain the adjusted pH-ORP coupling judgment logic, including:

[0038] Obtain the set of identified dominant microbial community types and assess the contribution of each dominant microbial community.

[0039] Based on the dominant bacterial community type set and its contribution level, the combined influence pattern of the microbial community in the soil at this monitoring depth on the pH value and the ORP value was determined.

[0040] Based on this comprehensive impact model, the corresponding logical adjustment rule is searched in the preset logical adjustment rule library;

[0041] Based on the found logic adjustment rule, the preset pH-ORP coupling judgment logic is adjusted.

[0042] Secondly, this 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:

[0043] The acquisition module is used to acquire the pH value of the soil at at least one monitoring depth and its corresponding soil redox potential (ORP) value;

[0044] The comparison and evaluation module is used to compare the pH value at the at least one monitoring depth with the target pH range at the monitoring depth and obtain the comparison result; evaluate the status and trend of the ORP value relative to the ORP reference range at the monitoring depth and obtain the evaluation result.

[0045] The judgment module is used to determine the dominant mode of change in soil pH at the monitoring depth based on the comparison results, evaluation results, and preset pH-ORP coupling judgment logic; the dominant mode of change includes chemical action and microbial metabolic activity.

[0046] The adjustment and feedback module is used to adjust the remediation agent application strategy for soil pH regulation at the monitoring depth according to the dominant mode of change, so as to perform pH adjustment.

[0047] Beneficial effects: First, this application can accurately distinguish between chemically and microbially dominant factors in soil pH changes, thus avoiding misjudgments caused by incomplete information in existing technologies. When pH changes are caused by microbial activity, the system will not blindly increase the dosage of remediation agents, but will adjust the remediation agent dosage strategy according to the characteristics of microbially mediated pH changes. Second, this precise judgment and strategy adjustment effectively solves the problem of excessive use of remediation agents, significantly reduces remediation costs, and reduces the secondary environmental risks that may be caused by excessive remediation agent dosage. Furthermore, by integrating the dynamic feedback of biogeochemical processes into the pH adjustment strategy, this application makes the soil remediation process more intelligent and adaptive. Especially in remediation projects where the restoration of indigenous microbial ecological functions is an important goal, this application can better support the growth and reproduction of microorganisms, improving bioremediation efficiency and long-term stability. Attached Figure Description

[0048] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of the present invention and should not be regarded as a limitation on the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0049] Figure 1 This is a schematic flowchart of the pH adjustment method for soil remediation disclosed in an embodiment of the present invention;

[0050] Figure 2 This is a schematic diagram of the pH adjustment system for soil remediation disclosed in an embodiment of the present invention. Detailed Implementation

[0051] Exemplary embodiments will now be described more fully with reference to the accompanying drawings. However, these exemplary embodiments can be implemented in many forms and should not be construed as limited to the examples set forth herein; rather, they are provided so that this embodiment will be more comprehensive and complete, and will fully convey the concept of the exemplary embodiments to those skilled in the art.

[0052] It should be noted that "multiple" as mentioned in this article refers to two or more.

[0053] Traditional existing soil remediation pH feedback systems, in applications aimed at restoring local microbial ecosystems and reducing contaminant concentrations, primarily rely on chemical buffering and reaction kinetic models to guide remediation agent dosing. However, this system faces a challenge: the introduction of remediation agents, while directly affecting pH chemically, also impacts the local microbial community in multiple ways.

[0054] For example, suppose a soil remediation project is being carried out on a site contaminated with both 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 the fixation of heavy metals. To this end, a multi-depth online pH monitoring and feedback control system was deployed. This system collects pH data at different depths using sensors and calculates the dosage of a calcareous amendment based on a soil chemical buffering model and a remediation agent reaction kinetic model. Initially, the system adds the amendment according to the chemical model's instructions, and the pH gradually rises. However, after the pH initially reaches the target range and remains there for a period, the pH at some monitoring points begins to fluctuate unexpectedly, even falling back into the acidic range, despite the system continuing to add the amendment. After investigating the system, no abnormalities were found in the sensor and amendment distribution. Further analysis revealed that the added amendment altered the soil microenvironment, affecting the metabolic activity of local microorganisms. For example, some acid-producing microorganisms become active again after environmental changes, and the organic acids they produce cause a local pH decrease. The current feedback system, based solely on the chemical model, interprets this microorganism-mediated pH decrease as insufficient remediation effect, thus instructing continued amendment addition.

[0055] Faced with the aforementioned problems, this embodiment first considered improving the soil chemical buffering model to better predict the chemical reaction effects of remediation agents. However, this method still cannot address the hysteretic and nonlinear effects of microbial activity on pH values.

[0056] To address this, this embodiment proposes a pH feedback method for soil pollution remediation, such as... Figure 1 As shown, the method in this embodiment includes:

[0057] S101, obtain the pH value of the soil at at least one monitoring depth and the corresponding soil redox potential (ORP) value;

[0058] S102, compare the pH value at the at least one monitoring depth with the pH target range at that monitoring depth, and obtain the comparison result; evaluate the state and trend of the ORP value relative to the ORP reference range at that monitoring depth, and obtain the evaluation result;

[0059] S103, based on the comparison results, evaluation results, and preset pH-ORP coupling judgment logic, determine the dominant mode of change in soil pH at the monitoring depth; the dominant mode of change includes chemical action and microbial metabolic activity.

[0060] S104, Based on the dominant change mode, adjust the remediation agent application strategy for soil pH adjustment at the monitoring depth to perform pH adjustment.

[0061] In the field of soil remediation, pH and oxidation-reduction potential (ORP) are two key physicochemical parameters that together reflect the biogeochemical state of the soil microenvironment. pH measures soil acidity and alkalinity, directly affecting the solubility and mobility of pollutants, as well as the activity of microorganisms. ORP characterizes the intensity and direction of redox reactions in the soil and is closely related to soil oxygen content, organic matter decomposition, heavy metal valence state changes, and microbial metabolic activity. The method proposed in this application aims to achieve precise control of soil pH adjustment through the synergistic analysis of these two parameters.

[0062] Specifically, soil remediation typically takes place at a specific contaminated site, which may contain contaminated layers at varying depths. Therefore, monitoring of soil parameters usually needs to be conducted at multiple depths. The pH target range refers to the ideal pH range set according to the remediation objectives. For example, for heavy metal pollution, the pH may need to be adjusted to neutral or slightly alkaline to promote heavy metal fixation. The ORP reference range, on the other hand, is a pre-defined ORP range based on soil type, contamination characteristics, and remediation objectives, used to assess whether the soil's redox state is suitable.

[0063] The pH-ORP coupling judgment logic is the core of this application. It presupposes a series of rules to correlate pH value, ORP value, and their changing trends to determine the main driving factors of soil pH changes. These driving factors are divided into chemically driven and microbial metabolic activities driven. Chemically driven typically refers to the direct acid-base neutralization, precipitation, or dissolution reactions between the remediation agent and soil components. Microbial metabolic activities driven refer to the indirect or direct influence of soil microbial communities on soil pH through their life activities (such as organic acid production, nitrification, denitrification, sulfate reduction, etc.). The remediation agent application strategy refers to the scheme of adjusting the type, dosage, frequency, and method of application of the remediation agent according to the determined dominant mode of pH change.

[0064] This application provides a pH adjustment method for soil remediation, the specific implementation of which can be described as follows. First, the method includes acquiring the pH value and corresponding soil redox potential (ORP) value at at least one monitoring depth in the soil. 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 (0-30 cm, 30-60 cm, 60-90 cm, etc.) at multiple representative locations in the contaminated area. These sensors can periodically collect data, for example, once per hour or per day, and transmit the collected pH and ORP values ​​to a data processing unit. As a preferred embodiment, soil samples can also be manually collected from different monitoring depths and measured in a laboratory using pH meters and ORP meters to obtain the corresponding pH and ORP values.

[0065] Secondly, the method includes comparing the pH value at the at least one monitoring depth with the target pH range at that monitoring depth to obtain a comparison result; and evaluating the state and trend of the ORP value relative to the ORP reference range at that monitoring depth 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 pre-set target pH 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 too low. For the ORP value, it can be compared with a preset ORP reference range to evaluate whether its current state is oxidizing, reducing, or neutral. At the same time, by analyzing historical ORP data, the trend of ORP value changes can be calculated, such as whether it is rising, falling, or remaining stable. These comparisons and evaluations can be automatically completed in the data processing unit through a preset algorithm, generating corresponding comparison and evaluation results.

[0066] Furthermore, the method includes determining the dominant mode of change in soil pH at the monitoring depth based on the comparison results, evaluation results, and a preset pH-ORP coupling judgment logic; the dominant mode of change includes chemical action and microbial metabolic activity. After obtaining the comparison results of pH and the evaluation results of ORP, the system calls the preset pH-ORP coupling judgment logic. This logic can be a decision tree model or a rule base, which contains the correspondence between pH, ORP and their changing trends and the dominant mode of pH change. For example, if the pH is low and the ORP continues to decrease, accompanied by the production of reducing gases such as hydrogen sulfide, it may indicate that microbial metabolic activity (such as sulfate-reducing bacteria) dominates the pH change. If the pH is low but the ORP does not change much, and the pH rises rapidly after the remediation agent is added, it may indicate that chemical action dominates. By applying this logic, the system can intelligently determine whether the main driving factor of the change in soil pH at the current monitoring depth is chemical action or microbial metabolic activity.

[0067] Finally, the method includes adjusting the remediation agent application strategy for soil pH regulation at the monitoring depth based on the dominant mode of change, in order to perform pH adjustment. Once the dominant mode of pH change is determined, the system can optimize the remediation agent application strategy based on this information. For example, if it is determined to be dominated by chemical action, the dosage and frequency of the remediation agent can be calculated according to traditional stoichiometry models. If it is determined to be dominated by microbial metabolic activity, it may be necessary to adjust the type of remediation agent, such as selecting an agent with less impact on specific microbial communities, or simultaneously adding microbial nutrients to promote the growth of beneficial microorganisms, thereby indirectly regulating the pH. In addition, the application method can be adjusted, for example, by using small-batch, multi-stage applications to avoid drastic disturbance to the microbial community. Thus, more targeted remediation measures can be taken based on the actual biogeochemical state of the soil, achieving precise pH regulation.

[0068] The key feature of this embodiment is the introduction of a pre-defined pH-ORP coupling judgment logic. This logic comprehensively analyzes the comparison results of pH values ​​and the evaluation results of ORP values ​​to intelligently determine the dominant mode of change in soil pH at the current monitoring depth—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 reducing change or a specific trend, the system may determine that microbial metabolic activity is dominant, because the acid-producing or alkali-producing metabolic processes of many microorganisms are accompanied by changes in redox state. Conversely, if the pH value change is highly consistent with the chemical reaction kinetics of the remediation agent, and the ORP value change is not significant or conforms to the expectations of a purely chemical reaction, it may be determined that chemical action is dominant. Once the dominant mode of pH value change is determined, the system can adjust the remediation agent application strategy for regulating soil pH at that monitoring depth based on this judgment. For example, if chemical action is determined to be dominant, the focus can be on the chemical neutralization capacity and diffusion efficiency of the remediation agent. If the problem is determined to be dominated by microbial metabolic activity, it may be necessary to consider adjusting the type of remediation agent to avoid inhibiting beneficial microorganisms, or supplementing with microbial nutrients to promote the growth of the target microbial community, thereby indirectly or synergistically regulating pH through biological pathways. Therefore, the method of this application overcomes the limitations of traditional methods that rely solely on chemical models, achieving biochemical synergistic regulation of soil pH, significantly improving the accuracy, efficiency, and sustainability of remediation, and avoiding the problems of excessive use of remediation agents or insufficient remediation.

[0069] This application further proposes the following steps for determining the dominant mode of soil pH change at the monitoring depth:

[0070] Based on the comparison results, evaluation results, and preset pH-ORP coupling judgment logic, a preliminary judgment is made to obtain a preliminary judgment result;

[0071] When the preliminary judgment result indicates that multiple microbial metabolic activities jointly affect the pH value, or indicates that multiple microbial metabolic activities jointly act on the soil, causing the pH value and the ORP value to change in a non-preset pattern, the dominant bacterial community type in the soil at that monitoring depth is identified.

[0072] Based on the identified dominant bacterial group type, the preset pH-ORP coupling judgment logic is adjusted to obtain the adjusted pH-ORP coupling judgment logic.

[0073] Based on the comparison results, evaluation results, and the adjusted pH-ORP coupling judgment logic, the dominant mode of soil pH change at this monitoring depth is determined.

[0074] The initial identification process involves using a pre-defined, universal pH-ORP coupling logic to perform an initial analysis of soil pH and ORP monitoring data to quickly identify potential dominant factors in pH changes. Specifically, when the initial identification results indicate that multiple microbial metabolic activities jointly affect the pH value, or that multiple microbial metabolic activities act on the soil, causing non-preset patterns of pH and ORP changes, the system further identifies the dominant microbial community types in the soil at that monitoring depth. This step aims to delve into the biological roots of complex or abnormal pH-ORP change patterns, providing precise biological evidence for subsequent logic adjustments by identifying specific dominant microbial populations. Based on this, the pre-defined pH-ORP coupling logic is adjusted according to the identified dominant microbial community types, resulting in an adjusted pH-ORP coupling logic. This adjustment process allows the logic to better adapt to the microbial activity characteristics of specific soil environments, improving the accuracy and specificity of the judgment. Finally, based on the comparison results, evaluation results, and the adjusted pH-ORP coupling logic, the dominant mode of pH change at that monitoring depth can be determined more accurately.

[0075] In some preferred embodiments, assuming that in soil at a certain monitoring depth, preliminary results show a continuous decrease in pH while the ORP value shows no significant change, and this pattern does not completely match the typical chemical action or single microbial activity pattern in the preset pH-ORP coupling judgment logic, the system will trigger the dominant microbial community identification process. Through gene sequencing or metabolite analysis, the system identifies a large number of sulfur-reducing bacteria (SRBs) in the soil as the dominant microbial community. It is known that sulfur-reducing bacteria metabolize to produce hydrogen sulfide under anaerobic conditions, which leads to a decrease in pH. Based on this identification result, the preset pH-ORP coupling judgment logic will be adjusted, for example, by increasing the weight of the relationship between sulfur-reducing bacterial metabolites (such as hydrogen sulfide) and pH and ORP values, or by introducing a new judgment branch to specifically handle pH decreases dominated by sulfur-reducing bacteria. The adjusted logic will be able to more accurately determine that the current dominant mode of pH decrease is dominated by microbial metabolic activity, and further refine it to the activity of sulfur-reducing bacteria. Therefore, the remediation agent application strategy can more precisely target the inhibition of sulfur-reducing bacteria activity or the neutralization of their metabolites, rather than blindly adjusting the pH spectrum, thereby achieving more efficient and economical soil remediation.

[0076] In some implementations, when preliminary results indicate that multiple microbial metabolic activities jointly affect pH, or that multiple microbial metabolic activities act on the soil, causing pH and ORP values ​​to change in a non-preset pattern, it is necessary to identify the dominant microbial community types in the soil at that monitoring depth. Specifically, identifying the dominant microbial community types in the soil at that monitoring depth may include the following steps:

[0077] The dominant microbial populations in the soil at the monitoring depth that exceed a preset threshold in terms of quantity or biomass are identified as the dominant microbial populations, and the identification information of the dominant microbial populations is obtained. The identification information includes the type of the dominant microbial population and the known influence patterns of the dominant microbial populations on the pH and ORP values ​​of the soil.

[0078] Identifying dominant microbial populations can be achieved through various 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 quantity of each microbial population in the sequencing results, microbial populations with a quantity or biomass exceeding a preset threshold can be screened. The preset threshold can be set based on empirical values, historical data, or specific remediation goals. The identification information of the dominant microbial populations can specifically include the taxonomic information of the microbial population (such as genus and species name) and its known influence patterns on soil pH and ORP during metabolism. For example, some microorganisms may cause a decrease in pH by producing acidic metabolites (such as lactic acid and acetic acid) or a decrease in ORP by reducing nitrates and sulfates. These known influence patterns can be derived from published literature, databases, or laboratory research data.

[0079] Based on each dominant microbial population, and considering its known influence patterns on the pH and ORP values ​​of the soil, combined with the current pH and ORP change directions at at least one monitoring depth, the contribution of the dominant microbial population to the current pH and ORP changes is assessed; the pH and ORP change directions include increasing, decreasing, and stable.

[0080] Specifically, for each identified dominant microbial population, its known influence patterns on pH and ORP are compared with the actual direction of change (increasing, decreasing, or remaining stable) of currently monitored soil pH and ORP. For example, if a dominant microbial population is known to decrease pH and increase ORP, and current monitoring data shows that pH is decreasing and ORP is increasing, it can be preliminarily determined that this microbial population has a high contribution to the current change. 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 matching degree and influence intensity.

[0081] Based on the degree of contribution, one or more dominant microbial populations that play a leading role in the current changes in pH and ORP are identified as the dominant bacterial population types.

[0082] Therefore, after assessing the contribution of all dominant microbial populations, one or more microbial populations that contribute the most to changes in the current pH and ORP values ​​can be selected based on preset discrimination rules. For example, a contribution threshold can be set, and all microbial populations whose contributions exceed this threshold can be identified as dominant bacterial groups. These identified dominant bacterial groups will be used to subsequently adjust the pH-ORP coupling judgment logic to more accurately guide the remediation agent dosage strategy.

[0083] This application further proposes steps for assessing the contribution of the dominant microbial population to the current changes in pH and ORP, including:

[0084] Based on the current dominant microbial population, and considering its known influence patterns on the pH and ORP values ​​of the soil, combined with the current direction of pH and ORP changes at at least one monitoring depth, an initial contribution assessment of the current dominant microbial population to the current changes in the pH and ORP values ​​is obtained.

[0085] Obtain information on synergistic and / or antagonistic effects 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 pH and ORP based on the initial contribution assessment and the synergistic and / or antagonistic effect information.

[0086] Specifically, obtaining an initial assessment of the contribution of the current dominant microbial population to the changes in pH and ORP values ​​refers to pre-establishing a typical influence pattern of the 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 and causing a decrease in ORP; while other microorganisms may cause an increase in pH through ammoniation or affect ORP through redox reactions. Combining the actual direction of pH and ORP changes (increasing, decreasing, or remaining stable) obtained from the current monitoring depth, a preliminary assessment can be made of the potential contribution of the dominant microbial population to the current changes. For example, if a known acid-producing microorganism is present and the current pH is decreasing, it is preliminarily assessed that it contributes to the decrease in pH.

[0087] Furthermore, obtaining information on synergistic and / or antagonistic interactions between the current dominant microbial population and one or more other dominant microbial populations refers to identifying and quantifying interactions within the microbial community. Synergistic information may include, for example, one microorganism's metabolites serving as substrates for another, or multiple microorganisms jointly participating in a complex biogeochemical cycle, thereby enhancing their impact on pH or ORP. For instance, anaerobic ammonia-oxidizing bacteria and methanogens may synergistically influence the nitrogen and carbon cycles, jointly affecting the soil's redox state. Antagonistic information may include, for example, one microorganism producing antibiotics that inhibit the growth of other microorganisms, or competing for limited nutrients, thereby weakening the impact of other microorganisms on pH or ORP. For example, certain fungi may secrete substances that inhibit bacterial growth, thus indirectly affecting bacterial-dominated pH changes. This synergistic and / or antagonistic information can be obtained from existing microbiological databases, literature studies, or through experimental analysis.

[0088] Therefore, determining the contribution of a dominant microbial population to the changes in the current pH and ORP values ​​based on the initial contribution assessment, the synergistic effect information, and / or antagonistic effect information implies a correction and optimization of the preliminary assessment results. For example, if the initial contribution assessment of a microorganism shows that it has a significant impact on the pH value, but there is also a dominant bacterial group with a strong antagonistic effect, its actual contribution may be lowered. Conversely, if there is a dominant bacterial group with a strong synergistic effect, its contribution may be higher. This correction makes the contribution assessment of a single dominant microbial population more closely reflect the actual soil microecological environment.

[0089] This application further proposes a method for determining the contribution of dominant microbial populations to changes in current pH and ORP values ​​based on synergistic and / or antagonistic information. The specific implementation includes:

[0090] Obtain a first current value of one or more synergistic indicators characterizing the strength of the synergistic effect; determine a first degree of contribution based on the first current value and the initial contribution assessment; and use the first degree of contribution as the degree of contribution of the current dominant microbial population to the current changes in the pH value and the ORP value.

[0091] And / or, obtain a second current value of one or more antagonistic indicators characterizing the strength of the antagonistic effect; determine a second degree of contribution based on the second current value and the initial contribution assessment; and use the second degree of contribution as the degree of contribution of the current dominant microbial population to the current changes in the pH value and the ORP value.

[0092] Specifically, synergistic indicators can be biomarkers or metabolites that indicate mutually reinforcing interactions between two or more microbial populations. For example, certain microorganisms, when coexisting, secrete specific enzymes, cofactors, or signaling molecules that can accelerate or enhance each other's metabolic activities, thereby synergistically affecting soil pH or ORP. The first current measure 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 mutually inhibiting interactions between microbial populations. For example, some microorganisms produce antibiotics, organic acids, or other inhibitory substances that limit the growth or metabolic activity of other microorganisms, thus affecting soil pH or ORP. The second current measure refers to the value obtained by quantitatively measuring these antagonistic indicators at the current monitoring depth, such as the concentration of an inhibitory compound or the expression level of a related gene. Initial contribution assessment refers to the preliminary judgment of the potential contribution of a dominant microbial population to the current changes in pH and ORP, based on the known influence patterns of the dominant microbial population on pH and ORP and the current direction of pH and ORP changes, before considering synergistic and / or antagonistic effects. After obtaining a first or second current value, this value is used to revise the initial contribution assessment. For example, if the first current value of a synergistic indicator is high, it indicates that the actual contribution of the dominant microbial population may be higher than the initial assessment, and therefore the first contribution level will be adjusted accordingly. Conversely, if the second current value of an antagonistic 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 pre-defined mathematical model, weighting factors, or machine learning-based algorithms to accurately quantify the impact of synergistic or antagonistic effects on the actual contribution.

[0093] This application addresses the challenge of accurately assessing the contribution of a single dominant microbial community to changes in soil pH and ORP in complex microbial communities by introducing quantitative measurements of synergistic and / or antagonistic indicators and revising the initial contribution assessment of dominant microbial populations based on these values. Specifically, when multiple microbial metabolic activities jointly influence pH or cause unpredictable changes in pH and ORP, traditional preliminary assessments based on known influence patterns may fail to fully capture the complex interactions between microorganisms. By obtaining current values ​​characterizing the strength of synergistic or antagonistic interactions, the actual impact of these interactions can be more accurately reflected. For example, if synergistic effects exist between two dominant microbial communities, the values ​​of their synergistic indicator will be enhanced; incorporating these values ​​into the contribution assessment more accurately reflects their actual driving force on pH and ORP changes. Conversely, if antagonistic effects exist, the values ​​of antagonistic indicators will be suppressed; incorporating these values ​​into the assessment avoids overestimating the contribution of any particular microbial community. Therefore, this method can transform the dynamic complexity of microbial communities into quantifiable parameters, enabling a more refined and accurate assessment of the contribution of dominant microbial communities. This provides a more reliable basis for subsequent adjustments to the pH-ORP coupling judgment logic, ultimately leading to more precise and effective formulation of soil pH adjustment strategies, significantly improving the targeting and success rate of soil remediation.

[0094] In some preferred embodiments, it is assumed that preliminary assessments at a certain monitoring depth in the soil show that *Denitrifying Bacillus* has a major contribution to the decrease in pH and the increase in ORP. However, further analysis reveals the presence of *Sulfur-Reducing Bacillus* in the soil, and it is known that *Denitrifying Bacillus* and *Sulfur-Reducing Bacillus* have a synergistic effect, jointly promoting the degradation of organic matter and producing acidic substances. To more accurately assess the contribution of *Denitrifying Bacillus*, this application obtains a first current value of one or more synergistic indicators characterizing the strength of this synergistic effect. 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 the two bacterial communities. If the first current value of these organic acids is high, it indicates a strong synergistic effect, and the initial contribution assessment of *Denitrifying Bacillus* is adjusted upwards to a higher first contribution level. Conversely, if *Nitrifying Bacillus* is found in the soil, and it is known that there may be antagonistic effects between *Denitrifying Bacillus* and *Nitrifying Bacillus* (e.g., competition for nitrogen sources), this application obtains a second current value of one or more antagonistic indicators characterizing the strength of this antagonistic effect. For example, the concentration of nitrite or nitrate in the soil can be measured; these are products of nitrifying bacteria metabolism. Higher secondary values ​​indicate stronger antagonism, and the initial contribution assessment of *Denitrifying Bacillus* may be downgraded, resulting in a lower secondary contribution. This method allows for a more accurate determination of the actual contribution of *Denitrifying Bacillus* in the current soil environment, providing more refined guidance for subsequent remediation agent application strategies.

[0095] This application further proposes a method for obtaining a first current value of one or more synergy indicators characterizing the strength of synergy, the steps of which include:

[0096] Obtain the initial values ​​of the one or more synergistic indicators in the soil at the current monitoring depth;

[0097] For the current monitoring depth, at least one interference reference value is obtained. The interference reference value is used to characterize the known influence of the soil matrix characteristics on the value of the synergistic indicator, or to characterize the known influence of other non-synergistic microbial activities in the soil on the value of the synergistic indicator, or to characterize the known influence of abiotic factors on the value of the synergistic indicator.

[0098] Based on the acquired initial value and the acquired at least one interference reference value, the initial value is corrected to obtain a corrected value; the obtained corrected value is used as the first current value of the one or more synergy indicators characterizing the strength of the synergy.

[0099] 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 using conventional soil analysis methods, such as chemical analysis and bioassay. These indicators can be microbial metabolites, enzyme activities, specific gene expression levels, etc., and their values ​​should ideally directly reflect the strength of the synergistic effect.

[0100] Obtaining at least one interference reference value is crucial to this scheme. An interference reference value can be understood as the quantification of factors that exert non-synergistic effects on the value of synergistic indicators. These factors include, but are not limited to, the physicochemical properties of the soil (such as soil texture, organic matter content, ionic strength, etc.), 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 influence of abiotic environmental factors (such as temperature, humidity, light, pollutant concentration, etc.) on the stability and detection accuracy of the indicators. These interference reference values ​​can be obtained through pre-established models, historical data, or real-time measurements.

[0101] In practical applications, correcting the initial value based on the acquired initial value and at least one interfering reference value involves using a mathematical model or algorithm to remove biases caused by interfering factors from the initial value, thereby obtaining a corrected value that more closely approximates the true strength of the synergistic effect. For example, linear regression, multivariate analysis, or algorithms based on specific correction coefficients can be used for correction. The corrected value is considered the first current value characterizing the strength of the synergistic effect and is used for subsequent contribution assessments.

[0102] This application further proposes a method for determining an interference reference value, the method further comprising:

[0103] Parameters were measured for soil matrix characteristics, other non-synergistic microbial activities, and abiotic factors at the current monitoring depth.

[0104] Based on the parameter measurement results, determine the at least one interference reference value.

[0105] Specifically, based on the soil matrix characteristics at the current monitoring depth, soil physicochemical parameters that have a preset physical / chemical interaction relationship with the synergistic indicator values ​​can be measured. For example, if the synergistic indicator is a certain ion, the soil's cation exchange capacity (CEC), clay mineral content, and organic matter content can be measured. These parameters affect the adsorption, desorption, or migration of ions, thus affecting their actual quantity in the soil.

[0106] For other non-synergistic microbial activities, parameters characterizing the metabolic pathway activity or metabolites of the non-synergistic microorganisms can be measured. For example, if the synergistic indicator is a certain metabolic intermediate, and other non-synergistic microorganisms in the soil can also produce or consume this intermediate, the specific enzyme activity or the concentration of characteristic metabolites of these non-synergistic microorganisms can be measured to quantify their impact on the synergistic indicator.

[0107] For abiotic factors, environmental parameters that have a predetermined impact on the stability of synergistic indicators can be measured. For example, if a synergistic indicator is easily degraded 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 helps assess the direct impact of abiotic factors on the magnitude of synergistic indicators.

[0108] The proposed method comprehensively and quantitatively acquires information on various potential interfering factors affecting the values ​​of synergistic indicator by measuring parameters related to soil matrix characteristics, other non-synergistic microbial activities, and abiotic factors at the current monitoring depth. Based on these parameter measurement results, and using pre-defined physicochemical models, biogeochemical models, or empirical relationships, at least one interfering reference value can be accurately determined. This method ensures that the acquisition of the interfering reference value is based on actual soil environmental conditions and complex biogeochemical processes, thereby making subsequent corrections to the initial values ​​of the synergistic indicator more accurate and reliable.

[0109] In some preferred embodiments, a specific example is illustrated below. Suppose that during soil remediation, it is necessary to assess the synergistic effect of a certain acid-producing microorganism (e.g., thiobacillus), with sulfate ion concentration as an indicator of synergistic effect. However, various factors in the soil may affect the actual amount of sulfate ions. Specifically, for soil matrix characteristics at the current monitoring depth, the clay content and organic matter content of the soil can be measured. For example, clay minerals may adsorb sulfate ions, and the decomposition of organic matter may also affect its concentration. For other non-synergistic microbial activities, the activity of sulfate-reducing bacteria (SRB) in the soil or the abundance of their characteristic genes can be measured. SRB reduce sulfate to sulfides, thereby lowering sulfate concentration; this is a non-synergistic interference. For abiotic factors, soil temperature and moisture content can be measured. For example, high temperatures may accelerate the biodegradation or chemical transformation of sulfate, while moisture content affects ion migration and solubility. After obtaining the measurement results of these parameters, interference reference values ​​can be determined based on pre-set models or empirical data. For example, based on the measured clay content, the average adsorption of sulfate by clay under current conditions can be looked up or calculated as a reference value for interference caused by soil matrix characteristics. Based on the SRB activity measurement results, the rate of sulfate consumption by SRB under current conditions can be estimated as a reference value for interference caused by other non-synergistic microbial activities. Based on soil temperature and moisture content, the abiotic degradation or transformation 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 values, thereby obtaining a more accurate first current value characterizing the strength of the synergistic effect of thiobacilli.

[0110] Specifically, the measurement results of the above parameters may include a first measurement result, a second measurement result, and a third measurement result.

[0111] Specifically, parameters were measured for soil matrix characteristics, other non-synergistic microbial activities, and abiotic factors at the current monitoring depth, including:

[0112] Based on the aforementioned soil matrix characteristics, soil physicochemical parameters that have a preset physical / chemical interaction relationship with the synergistic indicator value are measured at the current monitoring depth to obtain a first measurement result;

[0113] For the other non-synergistic microbial activities, parameters characterizing the metabolic pathway activity / metabolites of the non-synergistic microorganism are measured at the current monitoring depth to obtain a second measurement result;

[0114] Regarding the aforementioned abiotic factors, environmental parameters that have a preset impact on the stability of the synergistic indicator are measured at the current monitoring depth to obtain a third measurement result.

[0115] Specifically, the first measurement result refers to the data obtained from soil physicochemical parameters that have a pre-defined physical / chemical relationship with the values ​​of synergistic indicator at the current monitoring depth. These parameters may include, but are not limited to, soil texture (such as the ratio of sandy soil, loam, and clay), organic matter content, cation exchange capacity (CEC), soil moisture content, and soil density. For example, some synergistic indicators may exhibit different activities or stability under specific soil textures or organic matter contents. By measuring these physicochemical parameters, the influence of the soil matrix on synergistic indicators can be quantified.

[0116] The second measurement result refers to data obtained by measuring parameters characterizing the metabolic pathway activities or metabolites of other non-synergistic microorganisms at the current monitoring depth. These parameters aim to reflect the activity level of non-synergistic microbial communities in the soil and their potential interference with synergistic indicators. For example, the concentrations of enzyme activities (such as nitrifying and denitrifying enzyme activities), specific metabolites (such as volatile fatty acids and sulfides), or the abundance or expression levels of specific non-synergistic microbial genes can be measured using molecular biology methods (such as qPCR). These measurements help identify and quantify the consumption, transformation, or inhibition of synergistic indicators by non-synergistic microorganisms.

[0117] The third measurement result refers to data obtained by measuring environmental parameters that have a predetermined impact on the stability of synergistic indicators at the current monitoring depth. These parameters are typically abiotic factors in the soil environment that can directly affect the physicochemical properties or biological activity of synergistic indicators. For example, soil temperature, redox potential (ORP), dissolved oxygen concentration, heavy metal ion concentration, salinity, or light intensity can be measured. Changes in these environmental parameters may lead to the degradation, inactivation, or speciation of synergistic indicators, thus affecting the accuracy of their values.

[0118] The proposed method, through detailed parameter measurements of soil matrix characteristics, other non-synergistic microbial activities, and abiotic factors, and by obtaining first, second, and third measurement results, can more comprehensively and accurately identify and quantify various interfering factors affecting the values ​​of synergistic indicator values. This provides reliable reference data for subsequent calibration of the initial values ​​of synergistic indicators, ensuring that the calibrated values ​​more accurately reflect the actual intensity of the synergistic effect. This refined measurement and calibration mechanism makes the assessment of synergistic effects between dominant microbial communities more accurate, thus providing a solid data foundation for adjusting the pH-ORP coupling judgment logic.

[0119] Specifically, the above-mentioned adjustment of 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:

[0120] Obtain the set of identified dominant microbial community types and assess the contribution of each dominant microbial community.

[0121] Based on the set of dominant bacterial community types and the degree of contribution, the comprehensive influence pattern of the microbial community in the soil at this monitoring depth on the pH value and the ORP value was determined.

[0122] Based on the comprehensive impact model, the corresponding logical adjustment rule is searched in the preset logical adjustment rule library;

[0123] Based on the found logic adjustment rules, the preset pH-ORP coupling judgment logic is adjusted.

[0124] The identification of dominant microbial community types refers to the process of identifying, during soil remediation, the dominant microbial populations in terms of quantity or biomass through microbial community analysis techniques such as high-throughput sequencing and qPCR. The types of these dominant microbial populations and their known influence patterns on soil pH and ORP are recorded. For each identified dominant microbial population, its specific contribution to changes in current soil pH and ORP needs to be assessed, which can be done by analyzing its metabolic pathways, products, and interactions with other microorganisms.

[0125] Furthermore, based on the set of dominant microbial community types and their respective contributions, the comprehensive influence pattern of the microbial community in the soil at this monitoring depth on the pH and ORP values ​​is determined. This means integrating all identified dominant microbial populations and their individual contributions to form a comprehensive model reflecting the influence of the entire microbial community on pH and ORP values. This comprehensive influence model can be a mathematical model, a logic decision tree, or a rule set based on expert knowledge, used to describe how different microbial activities collectively drive changes in pH and ORP values ​​under specific soil conditions.

[0126] Furthermore, based on the comprehensive influence model, the corresponding logical adjustment rule is searched in a pre-defined logical adjustment rule base. This logical adjustment rule base is a pre-established knowledge base containing pH-ORP coupling judgment logic adjustment schemes for different comprehensive influence models of microorganisms. For example, if the comprehensive influence model shows that the activity of a certain acid-producing bacterial group is enhanced under specific ORP conditions, then there may be a rule in the rule base indicating that the pH-ORP coupling judgment logic should be adjusted in similar situations to make it more inclined to consider the influence of microbial acid production.

[0127] Finally, based on the found logic adjustment rules, the preset pH-ORP coupling judgment logic is adjusted. This means that specific adjustment rules obtained from the rule base are applied to the current pH-ORP coupling judgment logic, so that it can more accurately reflect the impact of complex microbial metabolic activities in the soil on pH and ORP values. This adjustment may involve modifying the judgment threshold, changing the judgment priority, or introducing new judgment conditions.

[0128] This application's solution, through in-depth analysis of the types of dominant microbial communities in the soil and their contribution to pH and ORP values, can more accurately grasp the impact of microbial metabolic activities on soil pH changes. When preliminary judgment results indicate that multiple microbial metabolic activities jointly affect pH, or cause pH and ORP changes that deviate from the preset pattern, traditional pH-ORP coupling judgment logic may fail to accurately identify the dominant mode of pH change. By identifying the types of dominant microbial communities and assessing their contributions, a more realistic comprehensive influence model of the microbial community can be constructed. Based on this comprehensive influence model, corresponding adjustment rules are searched and applied from a preset logic adjustment rule library, enabling the pH-ORP coupling judgment logic to dynamically adapt to complex microbial environments, thereby avoiding inappropriate remediation agent application strategies due to misjudgment of the dominant mode of pH change. Therefore, this application can effectively improve the accuracy and efficiency of soil pH adjustment.

[0129] Furthermore, 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:

[0130] The acquisition module 201 is used to acquire the pH value of the soil at at least one monitoring depth and the corresponding soil redox potential (ORP) value.

[0131] The comparison and evaluation module 202 is used to compare the pH value at the at least one monitoring depth with the pH target range at that monitoring depth and obtain the comparison result; evaluate the state and trend of the ORP value relative to the ORP reference range at that monitoring depth and obtain the evaluation result.

[0132] The judgment module 203 is used to determine the dominant mode of change in soil pH at the monitoring depth based on the comparison results, evaluation results, and preset pH-ORP coupling judgment logic; the dominant mode of change includes chemical action and microbial metabolic activity.

[0133] The adjustment and feedback module 204 is used to adjust the remediation agent application strategy for soil pH adjustment at the monitoring depth according to the dominant change mode, so as to perform pH adjustment.

[0134] The specific embodiments described above further illustrate the purpose, technical solution, and beneficial effects of the present invention. It should be understood that the above description is only a specific embodiment 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 within the scope of protection of the present invention.

Claims

1. A method for adjusting pH value for soil remediation, characterized in that, The method includes: Obtain the pH value and the corresponding soil redox potential (ORP) value at at least one monitoring depth in the soil; Compare the pH value at the at least one monitoring depth with the target pH range at that monitoring depth to obtain the comparison result; evaluate the status and trend of the ORP value relative to the ORP reference range at that monitoring depth to obtain the evaluation result; Based on the comparison results, evaluation results, and the preset pH-ORP coupling judgment logic, the dominant mode of change in soil pH at this monitoring depth is determined; the dominant mode of change includes chemical action and microbial metabolic activity. Based on the dominant change pattern, the remediation agent application strategy for soil pH adjustment at this monitoring depth is adjusted to perform pH adjustment.

2. The pH adjustment method for soil remediation according to claim 1, characterized in that, The process of determining the dominant mode of soil pH change at the monitoring depth based on the comparison results, evaluation results, and preset pH-ORP coupling judgment logic includes: Based on the comparison results, evaluation results, and preset pH-ORP coupling judgment logic, a preliminary judgment is made to obtain a preliminary judgment result; When the preliminary judgment result indicates that multiple microbial metabolic activities jointly affect the pH value, or indicates that multiple microbial metabolic activities jointly act on the soil, causing the pH value and the ORP value to change in a non-preset pattern, the dominant bacterial community type in the soil at that monitoring depth is identified. Based on the identified dominant bacterial group type, the preset pH-ORP coupling judgment logic is adjusted to obtain the adjusted pH-ORP coupling judgment logic. Based on the comparison results, evaluation results, and the adjusted pH-ORP coupling judgment logic, the dominant mode of soil pH change at this monitoring depth is determined.

3. The pH adjustment method for soil remediation according to claim 2, characterized in that, Identify the dominant microbial community types in the soil at this monitoring depth, including: The dominant microbial populations in the soil at the monitoring depth that exceed a preset threshold in terms of quantity or biomass are identified as the dominant microbial populations, and the identification information of the dominant microbial populations is obtained. The identification information includes the type of the dominant microbial population and the known influence patterns of the dominant microbial populations on the pH and ORP values ​​of the soil. Based on each dominant microbial population, and considering its known influence patterns on the pH and ORP values ​​of the soil, combined with the current pH and ORP change directions at at least one monitoring depth, the contribution of the dominant microbial population to the current pH and ORP changes is assessed; the pH and ORP change directions include increasing, decreasing, and stable. Based on the degree of contribution, one or more dominant microbial populations that play a leading role in the current changes in pH and ORP are identified as the dominant bacterial population types.

4. The pH adjustment method for soil remediation according to claim 3, characterized in that, Assess the contribution of this dominant microbial population to the current changes in pH and ORP, including: Based on the current dominant microbial population, and considering its known influence patterns on the pH and ORP values ​​of the soil, combined with the current direction of pH and ORP changes at at least one monitoring depth, an initial contribution assessment of the current dominant microbial population to the current changes in the pH and ORP values ​​is obtained. Obtain information on synergistic and / or antagonistic effects 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 pH and ORP based on the initial contribution assessment and the synergistic and / or antagonistic effect information.

5. The pH adjustment method for soil remediation according to claim 4, characterized in that, Based on the synergistic and / or antagonistic information, the contribution of the dominant microbial population to the current changes in pH and ORP values ​​is determined, including: Obtain a first current value of one or more synergistic indicators characterizing the strength of the synergistic effect; determine a first degree of contribution based on the first current value and the initial contribution assessment; and use the first degree of contribution as the degree of contribution of the current dominant microbial population to the current changes in the pH value and the ORP value. And / or, obtain a second current value of one or more antagonistic indicators characterizing the strength of the antagonistic effect; determine a second degree of contribution based on the second current value and the initial contribution assessment; and use the second degree of contribution as the degree of contribution 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 for one or more synergy indicators characterizing the strength of the synergy includes: Obtain the initial values ​​of the one or more synergistic indicators in the soil at the current monitoring depth; For the current monitoring depth, at least one interference reference value is obtained. The interference reference value is used to characterize the known influence of soil matrix characteristics on the synergistic indicator value, or to characterize the known influence of other non-synergistic microbial activities in the soil on the synergistic indicator value, or to characterize the known influence of abiotic factors on the synergistic indicator value. Based on the acquired initial value and the acquired at least one interference reference value, the initial value is corrected to obtain a corrected value; the obtained corrected value is used as the first current value of the one or more synergy indicators characterizing the strength of the synergy.

7. The pH adjustment method for soil remediation according to claim 5, characterized in that, The method further includes: Parameters were measured for soil matrix characteristics, other non-synergistic microbial activities, and abiotic factors at the current monitoring depth. Based on the parameter measurement results, at least one interference reference value is determined.

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; Specifically, parameters are measured for the soil matrix characteristics, other non-synergistic microbial activities, and abiotic factors at the current monitoring depth, including: Based on the aforementioned soil matrix characteristics, soil physicochemical parameters that have a preset physical / chemical interaction relationship with the synergistic indicator value are measured at the current monitoring depth to obtain a first measurement result; For the other non-synergistic microbial activities, parameters characterizing the metabolic pathway activity / metabolites of non-synergistic microorganisms are measured at the current monitoring depth to obtain a second measurement result; Regarding the aforementioned abiotic factors, environmental parameters that have a preset impact on the stability of the synergistic indicator are measured at the current monitoring depth to obtain a third measurement result.

9. The pH adjustment method for soil remediation according to claim 2, characterized in that, Based on the identified dominant bacterial community type, the preset pH-ORP coupling judgment logic is adjusted to obtain the adjusted pH-ORP coupling judgment logic, including: Obtain the set of identified dominant microbial community types and assess the contribution of each dominant microbial community. Based on the set of dominant bacterial community types and the degree of contribution, the comprehensive influence pattern of the microbial community in the soil at this monitoring depth on the pH value and the ORP value was determined. Based on the comprehensive impact model, the corresponding logical adjustment rule is searched in the preset logical adjustment rule library; Based on the found logic adjustment rules, 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: The acquisition module is used to acquire the pH value of the soil at at least one monitoring depth and its corresponding soil redox potential (ORP) value; The comparison and evaluation module is used to compare the pH value at the at least one monitoring depth with the target pH range at that monitoring depth and obtain the comparison result; evaluate the status and trend of the ORP value relative to the ORP reference range at that monitoring depth and obtain the evaluation result. The judgment module is used to determine the dominant mode of change in soil pH at the monitoring depth based on the comparison results, evaluation results, and preset pH-ORP coupling judgment logic; the dominant mode of change includes chemical action and microbial metabolic activity. The adjustment and feedback module is used to adjust the remediation agent application strategy for soil pH adjustment at the monitoring depth according to the dominant change mode, so as to perform pH adjustment.

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