Polyphosphate reinforced Fenton-like loess remediation method based on carbonate buffering

Abstract

The invention relates to the technical field of environmental chemistry, in particular to a carbonate buffer-based polyphosphate enhanced Fenton-like loess remediation method, which comprises the following steps: carrying out gridding point distribution sampling on a loess site to be remedied, and measuring the pH value, carbonate content and target pollutant concentration of each sampling point; determining a repair response index RRI value of each sampling point; generating an RRI spatial distribution diagram of the site according to the RRI values of all the sampling points, and dividing the RRI spatial distribution diagram into a high RRI region and a low RRI region; different molar ratios of Fe (III) to polyphosphate and peroxide adding modes are set for the high RRI region and the low RRI region; monitoring in real time to obtain the pH value and oxidation reduction potential (ORP) of the soil system, and supplementing the Fe (III)-polyphosphate complexing solution; and sampling and measuring the residual concentration of pollutants in the soil, and correcting the response index weight data based on the actual pollutant removal rate. The repairing efficiency and stability of the high-carbonate loess are improved.

Description

Technical Field

[0001] This invention relates to the field of environmental chemistry technology, and in particular to a method for loess remediation based on carbonate-buffered polyphosphate-reinforced Fenton-like materials. Background Technology

[0002] The rapid development of industry, agriculture, and urbanization has led to a large influx of organic pollutants into the soil environment. Persistent organic pollutants (POPs), due to their recalcitrant nature, bioaccumulation, and potential biotoxicity, pose a serious threat to the ecological environment and human health. In the vast loess region, the unique soil-forming process endows the soil with typical characteristics of high pH and high carbonate content. This alkaline and carbonate-rich background condition significantly limits the effectiveness of existing pollution remediation technologies. Currently, chemical oxidation remediation technologies, especially advanced oxidation processes based on hydroxyl radicals, have received widespread attention due to their rapid reaction and thorough degradation. Traditional Fenton oxidation technology, as a representative example, can effectively degrade pollutants under acidic conditions, but in alkaline environments like loess, iron ions readily form hydroxide precipitates and become inactive, significantly reducing oxidation efficiency. To address the stability of iron ions under neutral to alkaline conditions, researchers have introduced various complexing agents, such as organic complexing agents like ethylenediaminetetraacetic acid (EDTA) or inorganic complexing agents like polyphosphates, to form soluble complexes with iron ions, aiming to expand the effective pH range of the Fenton reaction. However, these improved methods still face many challenges: organic complexing agents may introduce secondary pollution risks and have poor biodegradability; while inorganic polyphosphates have better environmental compatibility, their application strategies are often singular and fixed, lacking sufficient consideration of the spatial heterogeneity of contaminated sites, and are particularly difficult to adaptively address the continuous buffering effect of high carbonate content in loess on the reaction system and its quenching effect on reactive oxygen species. Furthermore, existing technologies mostly focus on the initial formulation of remediation agents, generally lacking real-time monitoring of key chemical parameters (such as redox potential and pH) and dynamic feedback control mechanisms based on monitoring results during the remediation process. This results in poor controllability of the remediation process and makes it difficult to ensure uniform and stable remediation effects throughout the contaminated area.

[0003] To address the technical challenges in remediating organically contaminated loess with high pH and high carbonate content, existing remediation methods suffer from the following shortcomings: First, fixed agent application patterns are incompatible with the significant heterogeneity of contaminated sites, making precise application based on the specific contamination level and geochemical background at each site impossible, easily leading to remediation blind spots or agent waste. Second, the remediation process is inherently a dynamic chemical process, particularly the decomposition of peroxides and the degradation of pollutants, which are constantly disrupted by the continuous consumption of reactive species by carbonates in the soil. Current technologies lack real-time tracking and intervention for this process, failing to replenish activators or adjust oxidant application strategies to maintain efficient oxidation capacity when reactivity declines. Third, existing solutions are mostly "one-off" remediation operations, failing to form a closed-loop system encompassing post-remediation effect evaluation and model parameter self-optimization. This prevents the remediation strategy from self-learning and optimizing in subsequent projects, limiting its application potential and long-term technical benefits in large-scale, complex sites. Therefore, there is an urgent need to develop a precise remediation method capable of intelligently sensing changes in the soil environment, adaptively adjusting remediation strategies, and continuously optimizing decision-making.

[0004] Chinese Patent Publication No. CN103316902A discloses an apparatus and method for photoelectric Fenton remediation of phthalic acid ester-contaminated soil and groundwater. The method includes elliptical electrode arrangements within the phthalic acid ester-contaminated soil area, with the central electrode positioned at the highest pollutant concentration. Both the central and outermost electrodes are cathode electrodes, and the elliptical area covers the entire contaminated area. The method improves upon traditional photoelectric Fenton methods by directly injecting an electrolyte solution and hydrogen peroxide into the soil, along with Fe generated at the anode. 2+ / Fe 3+ The hydrogen peroxide generated at the cathode directly establishes a photoelectric Fenton system in the soil, and ultraviolet light is used to irradiate the soil surface, decomposing phthalic acid esters in the soil surface layer. Therefore, the aforementioned photoelectric Fenton remediation device and method for phthalic acid ester contaminated soil and groundwater suffers from several drawbacks: it has strict requirements on soil pH, lacks adaptive regulation to address the buffering characteristics of high-carbonate, high-pH loess, and lacks real-time response and dynamic adjustment capabilities to soil heterogeneity during the remediation process. Summary of the Invention

[0005] Therefore, this invention provides a polyphosphate-reinforced Fenton-like loess remediation method based on carbonate buffering to overcome the problems of poor adaptability and uneven remediation in existing technologies for alkaline high-carbonate loess.

[0006] To achieve the above objectives, this invention provides a method for loess remediation based on carbonate-buffered polyphosphate-reinforced Fenton-like materials, comprising:

[0007] Step S1: The loess site to be remediated is divided into grids, and sampling points are set up in each region to obtain regional initial parameters. The regional initial parameters include initial pH value, carbonate content and target pollutant concentration. Based on the regional initial parameters and response index weights of each region, the remediation response index of each region is calculated.

[0008] Step S2: Based on the comparison results between the repair response index of each area of ​​the loess site to be repaired and the preset repair response index threshold, each area is divided into a high RRI zone and a low RRI zone. The dosage ratio of Fe(III) to polyphosphate and the peroxide addition mode for each area are determined according to the zone division. Specifically, the dosage ratio for the high RRI zone is the first molar ratio, and the addition mode is a one-time addition; the dosage ratio for the low RRI zone is the second molar ratio, and the addition mode is a batch addition.

[0009] Step S3: Mix the polyphosphate solution and Fe(III) solution evenly to obtain Fe(III)-polyphosphate iron complex solution. According to the area division of the loess site to be remediated, add the Fe(III)-polyphosphate iron complex solution to the organically contaminated loess, and then add the peroxide solution.

[0010] Step S4: Deploy sensor groups in each area of ​​the loess site to be restored. Based on the data continuously collected by the sensor groups, determine the process parameter status of each area. The process parameter status includes process pH value and redox potential value.

[0011] Step S5: Based on the process parameter status of each region and the corresponding dosing mode, determine the replenishment strategy of Fe(III)-polyphosphate complex solution for the region to be repaired, including replenishing Fe(III)-polyphosphate complex solution to one or more adjacent regions of the region to be repaired and replenishing Fe(III)-polyphosphate complex solution to the region to be repaired itself.

[0012] Step S6: After the remediation is completed, detect the residual concentration of soil pollutants in each area and calculate the actual pollutant removal rate; adjust the weight of the response index based on the actual pollutant removal rate.

[0013] Further, step S5 includes:

[0014] S51, when the process pH value of any region is less than the first pH threshold and the redox potential value is less than the first potential threshold, the region is determined to be a region to be repaired.

[0015] S52, obtain the trend of redox potential change in the area to be repaired within a preset historical time period;

[0016] S53, when the redox potential shows a continuous decreasing trend, it is determined that the area to be repaired is in a state of reaction inactivation;

[0017] S54, based on the determination of the reaction inactivation state of the area to be repaired, Fe(III)-polyphosphate complexing solution is added, wherein;

[0018] When the area to be repaired is determined to be in a state of reaction inactivation, Fe(III)-polyphosphate complex solution is added to one or more areas adjacent to the area to be repaired.

[0019] When the area to be repaired is not determined to be in a state of reaction inactivation, Fe(III)-polyphosphate complex solution is added to the area to be repaired.

[0020] Furthermore, in step S53, the trend of redox potential change being continuously decreasing is defined as having several consecutive sampling times within the preset historical time period, and the redox potential value at each sampling time being lower than the redox potential value at the previous sampling time.

[0021] Further, step S54 includes:

[0022] Step S541: Determine the set of all regions adjacent to the region to be repaired;

[0023] Step S542: Traverse the set of adjacent regions and select regions in which the process pH value is greater than the second pH threshold and the redox potential value is greater than the second potential threshold to form a qualified set of adjacent regions.

[0024] Step S543: Determine whether the set of qualified adjacent regions is an empty set;

[0025] Step S544: If the set of qualified adjacent regions is not empty, then Fe(III)-polyphosphate complex solution is added to all regions in the set.

[0026] If the set of qualified adjacent regions is empty, then Fe(III)-polyphosphate complex solution is added to the region to be repaired.

[0027] Further, in step S544, the actual amount of Fe(III)-polyphosphate complex solution added is determined based on the process parameter state of the added area and the corresponding peroxide addition mode, wherein: the basic addition amount is calculated based on the difference between the process pH value of the area to be repaired and the first pH threshold, and the basic addition amount is corrected according to the addition mode of the area to be repaired to obtain the actual addition amount.

[0028] Further, step S2 includes:

[0029] Step S21: Based on the comparison results between the repair response index of each area of ​​the loess site to be repaired and the preset repair response index threshold, each area is divided into a high RRI area and a low RRI area.

[0030] Step S22: Calculate the average repair response index based on the repair response index of all the high RRI regions;

[0031] Step S23: Determine the theoretical number of batches to be added based on the average repair response index;

[0032] Step S24: Correct the theoretical number of dosing batches based on the initial pH value of each low RRI zone, and determine the actual number of dosing batches for each low RRI zone corresponding to the batch dosing mode.

[0033] Furthermore, the polyphosphate is one or more of pyrophosphate, tripolyphosphate, trimetaphosphate, tetrapolyphosphate or hexametaphosphate.

[0034] Furthermore, the concentration of the polyphosphate solution is 5 mmol / L to 100 mmol / L; the concentration of the Fe(III) solution is 5 mmol / L to 50 mmol / L.

[0035] Furthermore, the molar ratio of Fe(III) to polyphosphate is 1:0.5 to 1:2.

[0036] Further, the peroxide is at least one of hydrogen peroxide, persulfate, or perdisulfate; the concentration of the peroxide is in the range of 50 mmol / L to 500 mmol / L, and the molar ratio of Fe(III) to the peroxide is 1:5 to 1:50.

[0037] Compared with existing technologies, the beneficial effects of this invention are as follows: by constructing a remediation response index model to accurately zonate heterogeneous loess sites, and by using a sensor network to monitor and control the remediation process in real time, this invention achieves efficient, stable, and adaptive remediation of a Fenton-like system in loess environments with high carbonate content and high pH value; it transforms the traditional static remediation scheme into a dynamically adjustable intelligent process, significantly improving the adaptability and reliability of the remediation system, and providing a new technical approach for the treatment of organic pollution under complex geological conditions.

[0038] Furthermore, this invention effectively overcomes the problem of uneven remediation caused by the spatial heterogeneity of loess by introducing a remediation response index model to scientifically zon the site and formulate differentiated remediation strategies. This method can automatically enhance reagent application in areas with high carbonate content and high pollution, which are difficult to remediate, while employing an economical model for areas with minimal background interference. Thus, while ensuring overall remediation effectiveness, it achieves optimized allocation and efficient utilization of remediation resources.

[0039] Furthermore, this invention effectively addresses the continuous consumption of active components by carbonates through real-time monitoring of key parameters such as redox potential and pH value during the remediation process and the establishment of a rapid feedback control mechanism. The system can automatically replenish the activating complexing solution when oxidizing capacity declines and promptly adjust the reagent ratio when pH fluctuates abnormally, thereby significantly maintaining the long-term high efficiency and stability of the reaction system and preventing mid-process failure.

[0040] Furthermore, this invention forms a complete closed-loop decision-making system by feeding back the post-remediation evaluation results to the remediation response index model and adaptively optimizing the model parameters. This design enables the remediation strategy to have the ability to learn and continuously improve, and its decision-making accuracy continuously improves with the accumulation of remediation experience. It is particularly suitable for large-area, multi-batch loess contaminated site remediation projects and has significant long-term technical advantages.

[0041] Furthermore, by integrating real-time sensing, dynamic control, and model optimization, this invention achieves precise management of the dosage of agents such as peroxides and iron-based activators. The agents are precisely added according to the actual remediation needs, effectively avoiding the problems of chemical reagent waste and soil structure damage caused by excessive addition and incomplete remediation caused by insufficient addition in traditional remediation, thus combining environmental friendliness and economy. Attached Figure Description

[0042] Figure 1 This is a flowchart of the loess remediation method based on carbonate buffered polyphosphate-reinforced Fenton-like material according to the present invention;

[0043] Figure 2 This is a flowchart of step S2 of the polyphosphate-reinforced Fenton-like loess remediation method based on carbonate buffering of the present invention;

[0044] Figure 3 This is a flowchart of step S5 of the polyphosphate-reinforced Fenton-like loess remediation method based on carbonate buffering of the present invention;

[0045] Figure 4 This is a flowchart of step S54 of the polyphosphate-reinforced Fenton-like loess remediation method based on carbonate buffering according to the present invention. Detailed Implementation

[0046] To make the objectives and advantages of the present invention clearer, the present invention will be further described below with reference to embodiments; it should be understood that the specific embodiments described herein are merely for explaining the present invention and are not intended to limit the present invention.

[0047] Preferred embodiments of the present invention will now be described with reference to the accompanying drawings. Those skilled in the art should understand that these embodiments are merely illustrative of the technical principles of the present invention and are not intended to limit the scope of protection of the present invention.

[0048] It should be noted that in the description of this invention, the terms "upper", "lower", "left", "right", "inner", "outer", etc., which indicate directions or positional relationships, are based on the directions or positional relationships shown in the accompanying drawings. This is only for the convenience of description and is not intended to indicate or imply that the device or element must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, it should not be construed as a limitation of this invention.

[0049] Furthermore, it should be noted that, in the description of this invention, unless otherwise explicitly specified and limited, the terms "installation," "connection," and "linking" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection of two components. Those skilled in the art can understand the specific meaning of the above terms in this invention according to the specific circumstances.

[0050] Please see Figure 1 The flowchart shown is a process for the loess remediation method based on carbonate buffered polyphosphate-reinforced Fenton-like material according to the present invention.

[0051] This invention provides a method for loess remediation based on carbonate-buffered polyphosphate-reinforced Fenton-like materials, comprising:

[0052] Step S1: The loess site to be remediated is divided into grids, and sampling points are set up in each region to obtain regional initial parameters. The regional initial parameters include initial pH value, carbonate content and target pollutant concentration. Based on the regional initial parameters and response index weights of each region, the remediation response index of each region is calculated.

[0053] In a specific embodiment, step S1 is implemented as follows: First, the loess site to be remediated is divided into 10m × 10m square areas using a grid-based sampling method. Soil samples are collected at a depth of 0-20cm at five points in the center and four corners of each area, and the samples are mixed thoroughly to serve as representative samples for that area. The initial pH value of the soil is determined using a pH meter (model: METTLER TOLEDO FE28); the carbonate content is determined by gas chromatography using a carbonate analyzer (model: Eijkelkamp 08.53), expressed as CaCO3 mass fraction; the concentration of the target pollutant (taking the polycyclic aromatic hydrocarbon phenanthrene as an example) is determined by gas chromatography-mass spectrometry (model: Agilent 8890-5977B). The specific formula for calculating the remediation response index is as follows:

[0054] ;

[0055] Wherein, w1 is the pH value weighting coefficient, dimensionless, ranging from 0 to 1, preferably w1 is 0.5; w2 is the carbonate content weighting coefficient, dimensionless, ranging from 0 to 1, preferably w2 is 0.3; w3 is the target pollutant concentration weighting coefficient, dimensionless, ranging from 0 to 1, preferably w3 is 0.2; pH i The initial pH value of the i-th region is dimensionless and ranges from 0 to 14, preferably with a typical value of 7.5 to 8.5; C i S represents the carbonate content of the i-th region, expressed as a percentage (%) of CaCO3 by mass, ranging from 0% to 100%, with a typical value of 5% to 15%; i For the target pollutant concentration in the i-th region, taking the polycyclic aromatic hydrocarbon phenanthrene as an example, the dimension is milligrams per kilogram (mg / kg), and the value ranges from 0 to 1000 mg / kg, with a typical value of 10 to 100 mg / kg; RRI i Let be the repair response index of the i-th region, which is dimensionless; e is the natural constant.

[0056] w1, w2, and w3 satisfy w1 + w2 + w3 = 1;

[0057] When pH i <5 or pH i When >10, in the formula Take 0.

[0058] Understandably, the parameters in the formula are set with clear physical meaning and dimensional consistency: the pH term uses symmetric normalization centered at 7.5, because Fenton-like reactions can still proceed effectively under weakly alkaline conditions through polyphosphate complexation, and the natural pH of loess is mostly concentrated in the range of 7.5–8.5; the carbonate term uses a linear normalization coefficient of 15, corresponding to the typical high value of carbonate content in loess; the pollutant term uses an exponential decay function, which reflects both the driving effect of pollutant concentration on remediation needs and avoids oversensitivity in extremely high concentration ranges. The allocation of weight coefficients reflects the order of importance of each parameter. pH conditions are given the highest weight due to their decisive role in iron speciation and reaction pathways, followed by carbonate buffering capacity, while pollutant concentration has a relatively low weight because it can be adapted by adjusting the dosage.

[0059] It is understandable that the inherent spatial heterogeneity of loess sites makes traditional uniform application methods inefficient. This invention introduces the remediation response index as a comprehensive criterion, transforming complex soil environmental parameters into comparable decision-making criteria. The special treatment of pH value fully considers the synergistic effect of the loess carbonate buffer system and the catalytic properties of polyphosphate complexed iron. When the soil is too acidic or too alkaline, even with the presence of carbonate buffer and polyphosphate complex, the reaction efficiency will still be significantly reduced. Therefore, setting the score to zero under this condition can effectively avoid misjudgment.

[0060] Step S2: Based on the comparison results between the repair response index of each area of ​​the loess site to be repaired and the preset repair response index threshold, each area is divided into a high RRI zone and a low RRI zone. The dosage ratio of Fe(III) to polyphosphate and the peroxide addition mode for each area are determined according to the zone division. Specifically, the dosage ratio for the high RRI zone is the first molar ratio, and the addition mode is a one-time addition; the dosage ratio for the low RRI zone is the second molar ratio, and the addition mode is a batch addition.

[0061] Specifically, the molar ratio of Fe(III) to polyphosphate is 1:0.5 to 1:2.

[0062] Specifically, step S2 includes:

[0063] Step S21: Based on the comparison results between the repair response index of each area of ​​the loess site to be repaired and the preset repair response index threshold, each area is divided into a high RRI area and a low RRI area.

[0064] In one specific embodiment, the repair response index threshold is set to 0.6. Regions with a repair response index greater than or equal to 0.6 are classified as high RRI regions, and regions with a repair response index less than 0.6 are classified as low RRI regions.

[0065] It is understood that the repair response index threshold is the criterion for regional division, is dimensionless, and ranges from 0.3 to 0.8. Preferably, the repair response index threshold is 0.6. This threshold is determined by the median or tertile of the repair response index of all regions of the site.

[0066] Step S22: Calculate the average repair response index based on the repair response index of all the high RRI regions;

[0067] In one specific embodiment, the arithmetic mean of all the repair response indices classified as high RRI regions is taken to obtain the average repair response index, denoted as RRI. a , dimensionless.

[0068] Understandably, high RRI areas, as representative of the best-condition areas on the site, better reflect the site's optimal remediation potential. By taking an average rather than a single extreme value, the excessive influence of individual abnormal areas on the overall strategy is avoided, ensuring the robustness of subsequent decisions.

[0069] Step S23: Determine the theoretical number of batches to be added based on the average repair response index;

[0070] In a specific embodiment, the formula for calculating the theoretical number of batches is as follows:

[0071] ;

[0072] It is understandable that N t k1 is the theoretical number of batches to be added, dimensionless, and an integer ranging from 2 to 5; k1 is the proportionality coefficient, dimensionless, ranging from -4 to -2, preferably -3; b is the baseline number of batches, dimensionless, ranging from 4 to 6, preferably 5.

[0073] Among them, the theoretical number of batches N t The calculation result is rounded to the nearest integer, and the final value is taken no less than 2 times and no more than 5 times.

[0074] Understandably, the theoretical number of application batches is negatively correlated with the average remediation response index (RRI). This is because a high RRI in high-RRI areas indicates superior overall site conditions and a robust carbonate buffer system. While low-RRI areas may have relatively poorer conditions, their environmental pressure is lower, and the reaction system is more stable. Therefore, fewer application batches can be used to complete the remediation, improving efficiency. Conversely, a low RRI in high-RRI areas indicates more severe overall site conditions. Low-RRI areas face greater environmental pressure, requiring more application batches to maintain the continuous activity of the reaction system and prevent system collapse due to excessive single application.

[0075] Step S24: Correct the theoretical number of dosing batches based on the initial pH value of each low RRI zone, and determine the actual number of dosing batches for each low RRI zone corresponding to the batch dosing mode.

[0076] In one specific embodiment, for each low RRI zone, its initial pH value pHi is obtained, and the absolute value of the deviation between this value and the optimal reaction pH value of 7.0 is calculated and denoted as |ΔpH|. Then, the theoretical number of dosing batches is corrected using the following formula to obtain the actual number of dosing batches:

[0077] ;

[0078] Where, N a The actual number of batches added is dimensionless and ranges from 2 to 8; |ΔpH| is the absolute value of the deviation between the initial pH value and the optimal reaction pH value of 7.0, which is dimensionless; α is the pH correction coefficient, dimensionless and ranges from 0.1 to 0.3, preferably 0.2.

[0079] Among them, the actual number of batches added N a The calculation result is rounded to the nearest integer, and the final value is no less than 2 and no more than 8.

[0080] Understandably, the actual number of addition batches is positively correlated with the degree of pH deviation from the optimal value. This is because in Fenton-like reaction systems, the pH environment has a decisive impact on the activity of the iron catalyst, the decomposition rate of peroxides, and the efficiency of free radical generation. When the initial pH value in the low RRI region deviates from the optimal reaction pH value, the reaction system faces greater environmental pressure, the catalyst is prone to deactivation, the peroxide decomposition pathway may change, and the free radical yield decreases. By increasing the number of addition batches, the reaction pressure can be dispersed, allowing the system sufficient time to self-regulate after each addition, avoiding rapid deactivation of the reaction system due to excessive addition in a single instance. The pH correction coefficient is set to consider both the importance of pH influence and the operational complexity caused by over-correction, ensuring that the remediation strategy is engineering feasible while maintaining effectiveness.

[0081] In one specific embodiment, for the high RRI region, the dosage ratio of Fe(III) to polyphosphate adopts a first molar ratio, preferably 1:1; for the low RRI region, the dosage ratio of Fe(III) to polyphosphate adopts a second molar ratio, preferably 1:1.5.

[0082] Understandably, the high RRI region possesses a good carbonate buffer system and a suitable acid-base environment. A 1:1 ratio of Fe(III) to polyphosphate ensures the formation of stable iron complexes, maintaining the catalyst's active state in the loess environment. The low RRI region has relatively harsh environmental conditions; increasing the polyphosphate ratio to 1:1.5 can enhance the complexation stabilization effect of iron ions and prevent catalyst deactivation under adverse environmental conditions.

[0083] Step S3: Mix the polyphosphate solution and Fe(III) solution evenly to obtain Fe(III)-polyphosphate iron complex solution. According to the area division of the loess site to be remediated, add the Fe(III)-polyphosphate iron complex solution to the organically contaminated loess, and then add the peroxide solution.

[0084] Specifically, the polyphosphate is one or more of the following: pyrophosphate, tripolyphosphate, trimetaphosphate, tetrapolyphosphate, or hexametaphosphate.

[0085] Specifically, the concentration of the polyphosphate solution is 5 mmol / L to 100 mmol / L; the concentration of the Fe(III) solution is 5 mmol / L to 50 mmol / L.

[0086] Specifically, the peroxide is at least one of hydrogen peroxide, persulfate, or perdisulfate; the concentration of the peroxide is in the range of 50 mmol / L to 500 mmol / L, and the molar ratio of Fe(III) to the peroxide is 1:5 to 1:50.

[0087] Step S4: Deploy sensor groups in each area of ​​the loess site to be restored. Based on the data continuously collected by the sensor groups, determine the process parameter status of each area. The process parameter status includes process pH value and redox potential value.

[0088] In one specific embodiment, a sensor array is deployed at the center of each area of ​​the loess site to be restored. This sensor array includes a pH composite electrode and a platinum-plate redox potential electrode. The sensors are connected to a data acquisition unit via waterproof cables. The data acquisition unit continuously collects data at a preset sampling frequency and transmits the data to the host computer software in the central control room via a wireless transmission module. The host computer software displays and stores the received data in real time and calculates the process parameter status values ​​for each area.

[0089] Specifically, the pH composite electrode is a sensor used to measure the pH value of soil pore water, with a measurement range of 0-14 and an accuracy of ±0.1; the redox potential electrode is a sensor used to measure the redox potential of soil, with a measurement range of -1000mV to +1000mV and an accuracy of ±10mV; the sampling frequency of the data acquisition device is set to collect data once every 10 minutes; the host computer software is developed using configuration software and has data storage, real-time display, and abnormal alarm functions.

[0090] Step S5: Based on the process parameter status of each region and the corresponding dosing mode, determine the replenishment strategy of Fe(III)-polyphosphate complex solution for the region to be repaired, including replenishing Fe(III)-polyphosphate complex solution to one or more adjacent regions of the region to be repaired and replenishing Fe(III)-polyphosphate complex solution to the region to be repaired itself.

[0091] Specifically, step S5 includes:

[0092] S51, when the process pH value of any region is less than the first pH threshold and the redox potential value is less than the first potential threshold, the region is determined to be a region to be repaired.

[0093] In one specific embodiment, process parameters of each region are monitored in real time. When the process pH value of a certain region is detected to be lower than 5.0 and the redox potential value of that region is lower than 400 mV, the system automatically marks the region as a region to be repaired and triggers the subsequent trend analysis process.

[0094] The first pH threshold is the threshold for determining the pH value of the process. It is dimensionless and ranges from 4.5 to 5.5, preferably 5.0. The first potential threshold is the threshold for determining the redox potential. It is in millivolts and ranges from 350 millivolts to 450 millivolts, preferably 400 millivolts.

[0095] Understandably, a decrease in process pH usually indicates the formation of acidic intermediates or the decomposition of peroxides producing hydrogen ions during the reaction. When the pH is too low, it severely affects the activity and stability of the iron catalyst. The redox potential directly characterizes the system's oxidizing capacity; a low potential indicates insufficient free radical generation or excessive consumption, suggesting the reaction system is losing its ability to oxidize and degrade pollutants. Using these two parameters in combination improves the accuracy of judgment, avoids misjudgments due to accidental fluctuations in a single parameter, and ensures that the replenishment procedure is only initiated when the reaction system shows significant deterioration. This design guarantees remediation effectiveness while avoiding unnecessary reagent waste.

[0096] S52, obtain the trend of redox potential change in the area to be repaired within a preset historical time period;

[0097] In one specific embodiment, when a region is identified as a region to be repaired, the system automatically extracts the redox potential monitoring data of that region over the past 60 minutes from the database. These data are arranged in chronological order to form a time series dataset of redox potentials for subsequent trend analysis.

[0098] It is understandable that the preset historical period is the time length taken for trend analysis, with the unit being minutes, and the value range being 30 minutes to 120 minutes, preferably 60 minutes.

[0099] It is understandable that redox potentials fluctuate naturally during the repair process, and a brief, single-point anomaly does not necessarily represent the true state of the reaction system. By observing the trend of data changes over a longer period, we can eliminate the interference of random factors and more accurately grasp the true evolution direction of the reaction system.

[0100] S53, when the redox potential shows a continuous decreasing trend, it is determined that the area to be repaired is in a state of reaction inactivation;

[0101] Specifically, in step S53, the trend of redox potential change being continuously decreasing is defined as having several consecutive sampling times within the preset historical time period, and the redox potential value at each sampling time being lower than the redox potential value at the previous sampling time.

[0102] In one specific embodiment, the system analyzes the redox potential time series data of the area to be repaired. When it is found that the redox potential value at each of the six consecutive sampling time points is strictly lower than the value at the previous time point, it is determined that the redox potential of the area is continuously decreasing, and thus the area is determined to be in a state of reaction inactivation.

[0103] It is understandable that the number of consecutive sampling time points is the minimum number of consecutive decreasing points required to determine a continuous downward trend. It is dimensionless and ranges from 4 to 8 points, with 6 points being the preferred value.

[0104] Understandably, a continuous decrease in redox potential indicates that the reaction system is undergoing an irreversible deterioration process, possibly due to gradual catalyst deactivation, continuous consumption of peroxides without replenishment, or the continuous accumulation of toxic intermediates. Requirement that the redox potential shows a decreasing trend at multiple consecutive time points effectively eliminates false signals caused by instrument noise, slight stirring disturbances, or instantaneous concentration fluctuations, ensuring that intervention measures are only triggered when the reaction system has indeed entered a state of continuous deterioration.

[0105] S54, based on the determination of the reaction inactivation state of the area to be repaired, Fe(III)-polyphosphate complexing solution is added, wherein;

[0106] When the area to be repaired is determined to be in a state of reaction inactivation, Fe(III)-polyphosphate complex solution is added to one or more areas adjacent to the area to be repaired.

[0107] When the area to be repaired is not determined to be in a state of reaction inactivation, Fe(III)-polyphosphate complex solution is added to the area to be repaired.

[0108] Specifically, step S54 includes:

[0109] Step S541: Determine the set of all regions adjacent to the region to be repaired;

[0110] In a specific embodiment, the adjacent areas in the four directions of east, south, west and north are obtained with the area to be repaired as the center, and these adjacent areas are combined into an adjacent area set; if the area to be repaired is located at the site boundary, only the existing adjacent areas are taken; the determination of the adjacent area set is based on the principle of spatial adjacency, and the areas in the diagonal direction are not considered.

[0111] Step S542: Traverse the set of adjacent regions and select regions in which the process pH value is greater than the second pH threshold and the redox potential value is greater than the second potential threshold to form a qualified set of adjacent regions.

[0112] In one specific embodiment, each region in the adjacent region set is traversed, and its process pH value is checked to be greater than 6.0, while its redox potential value is checked to be greater than 500 mV. Regions that meet both conditions are included in the qualified adjacent region set.

[0113] Understandably, the second pH threshold is the pH standard for screening qualified adjacent areas, which is dimensionless and ranges from 5.5 to 6.5, preferably 6.0; the second potential threshold is the redox potential standard for screening qualified adjacent areas, which is in millivolts and ranges from 450 millivolts to 550 millivolts, preferably 500 millivolts.

[0114] It is understandable that only adjacent regions with healthy reaction environments and sufficient reaction potential can effectively form new reaction fronts after receiving additional catalysts, and drive active species to diffuse into deactivated regions through concentration gradients. The high pH and redox potential requirements ensure that the selected regions have sufficient reaction driving force and suitable chemical environment, which can ensure that the added catalyst is used efficiently, rather than being rapidly deactivated in an unfavorable environment.

[0115] Step S543: Determine whether the set of qualified adjacent regions is an empty set;

[0116] Step S544: If the set of qualified adjacent regions is not empty, then Fe(III)-polyphosphate complex solution is added to all regions in the set.

[0117] If the set of qualified adjacent regions is empty, then Fe(III)-polyphosphate complex solution is added to the region to be repaired.

[0118] Specifically, in step S544, the actual amount of Fe(III)-polyphosphate complex solution added is determined based on the process parameter state of the added area and the corresponding peroxide addition mode. The basic addition amount is calculated based on the difference between the process pH value of the area to be repaired and the first pH threshold. The basic addition amount is then corrected according to the addition mode of the area to be repaired to obtain the actual addition amount.

[0119] In one specific embodiment, the difference between the process pH value of the area to be repaired and the first pH threshold of 5.0 is first calculated, and the basal replenishment amount is calculated based on this difference. The basal replenishment amount equals the difference multiplied by a unit replenishment factor, where the unit replenishment factor is taken as 0.5 liters of complexing solution per square meter per unit pH difference. Then, a correction is made according to the dosing mode of the area to be repaired: if the area to be repaired is subject to a one-time dosing mode, the correction factor is 1.2; if it is subject to a batch dosing mode, the correction factor is 0.8. The actual replenishment amount equals the basal replenishment amount multiplied by the correction factor.

[0120] It is understood that the basic supplement amount is the baseline supplement amount calculated based on the degree of pH deviation, with the dimension of liter. The calculation formula is: basic supplement amount = (first pH threshold - process pH value) × unit supplement coefficient; the unit supplement coefficient is the supplement amount coefficient corresponding to the pH difference, with the dimension of liter per pH unit per square meter, and the value range is 0.3 to 0.7, preferably 0.5; the correction coefficient is a coefficient adjusted according to the dosing mode, dimensionless. The correction coefficient for the one-time dosing mode ranges from 1.0 to 1.5, preferably 1.2, and the correction coefficient for the batch dosing mode ranges from 0.5 to 1.0, preferably 0.8.

[0121] Understandably, the difference between the process pH and the threshold directly reflects the degree to which the reaction system deviates from the ideal reaction environment. This deviation mainly stems from the accumulation of acidic intermediates and the depletion of carbonate buffer capacity during the reaction. A large negative pH deviation indicates that the reaction system has produced a significant amount of acidic substances. These acidic substances not only inhibit the activity of the iron catalyst but also alter the stability constant of polyphosphate complexes, leading to a decrease in catalytic efficiency. Calculating the basic replenishment amount based on this difference essentially estimates the amount of catalyst required to rebuild a suitable reaction environment based on the severity of system acidification. The design of different correction coefficients for different addition modes takes into account the differences in system kinetics. Regions corresponding to the one-time addition mode typically have better mass transfer conditions and higher contaminant concentration gradients, enabling faster dispersion and utilization of the added catalyst, thus requiring a larger replenishment amount. In contrast, regions corresponding to the batch addition mode often have mass transfer limitations, and excessively rapid catalyst replenishment may lead to excessively high local concentrations, causing agglomeration and deactivation, thus requiring a relatively conservative replenishment strategy.

[0122] Step S6: After the remediation is completed, detect the residual concentration of soil pollutants in each area and calculate the actual pollutant removal rate; adjust the weight of the response index based on the actual pollutant removal rate.

[0123] In one specific embodiment, step S6 is implemented as follows: After the remediation project is completed, soil samples from each area are collected again using the same grid sampling method as in step S1, and the residual concentration of the target pollutant is determined using gas chromatography-mass spectrometry. The actual pollutant removal rate is calculated by the ratio of the difference between the initial concentration and the residual concentration to the initial concentration. Based on the difference between the actual removal rate and the predicted removal rate in each area, the gradient descent method is used to correct the weights of the response index. The corrected weights are used for subsequent remediation predictions for similar sites.

[0124] Understandably, the actual pollutant removal rate is an evaluation index for remediation effectiveness, dimensionless, and calculated as (initial concentration - residual concentration) / initial concentration × 100%; the learning rate is a step size control parameter for weight correction, dimensionless, with a value range of 0.1 to 0.3, preferably 0.2; the normalization coefficient is a normalization parameter that ensures the total weight sum is 1, dimensionless.

[0125] Understandably, when there is a systematic deviation between the actual removal rate and the predicted value, it indicates that the initial weight allocation failed to accurately reflect the true impact of each environmental parameter on the remediation effect. Through iterative adjustment using the gradient descent method, the weight coefficients will gradually converge to values ​​that better reflect the actual interaction. This adaptive learning mechanism can effectively overcome the model applicability problem caused by regional differences in loess, enabling the remediation prediction model to continuously improve with the accumulation of engineering experience. The weight correction process essentially involves inverting the contribution of each environmental parameter through a large amount of actual engineering data, thereby establishing a more accurate assessment system for site remediation potential.

[0126] The technical solution of the present invention has been described above with reference to the preferred embodiments shown in the accompanying drawings. However, it will be readily understood by those skilled in the art that the scope of protection of the present invention is obviously not limited to these specific embodiments. Without departing from the principles of the present invention, those skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical solutions after these changes or substitutions will all fall within the scope of protection of the present invention.

Claims

1. A method for loess remediation based on carbonate-buffered polyphosphate-reinforced Fenton-like phosphorus, characterized in that, include: Step S1: The loess site to be remediated is divided into grids, and sampling points are set up in each region to obtain regional initial parameters. The regional initial parameters include initial pH value, carbonate content and target pollutant concentration. Based on the regional initial parameters and response index weights of each region, the remediation response index of each region is calculated. Step S2: Based on the comparison results between the repair response index of each area of ​​the loess site to be repaired and the preset repair response index threshold, each area is divided into a high RRI zone and a low RRI zone. The dosage ratio of Fe(III) to polyphosphate and the peroxide addition mode for each area are determined according to the zone division. Specifically, the dosage ratio for the high RRI zone is the first molar ratio, and the addition mode is a one-time addition; the dosage ratio for the low RRI zone is the second molar ratio, and the addition mode is a batch addition. Step S3: Mix the polyphosphate solution and Fe(III) solution evenly to obtain Fe(III)-polyphosphate iron complex solution. According to the area division of the loess site to be remediated, add the Fe(III)-polyphosphate iron complex solution to the organically contaminated loess, and then add the peroxide solution. Step S4: Deploy sensor groups in each area of ​​the loess site to be restored. Based on the data continuously collected by the sensor groups, determine the process parameter status of each area. The process parameter status includes process pH value and redox potential value. Step S5: Based on the process parameter status of each region and the corresponding dosing mode, determine the replenishment strategy of Fe(III)-polyphosphate complex solution for the region to be repaired, including replenishing Fe(III)-polyphosphate complex solution to one or more adjacent regions of the region to be repaired and replenishing Fe(III)-polyphosphate complex solution to the region to be repaired itself. Step S6: After the remediation is completed, detect the residual concentration of soil pollutants in each area and calculate the actual pollutant removal rate; adjust the weight of the response index based on the actual pollutant removal rate.

2. The loess remediation method based on carbonate buffering and polyphosphate-reinforced Fenton-like structure according to claim 1, characterized in that, Step S5 includes: S51, when the process pH value of any region is less than the first pH threshold and the redox potential value is less than the first potential threshold, the region is determined to be a region to be repaired. S52, obtain the trend of redox potential change in the area to be repaired within a preset historical time period; S53, when the redox potential shows a continuous decreasing trend, it is determined that the area to be repaired is in a state of reaction inactivation; S54, based on the determination of the reaction inactivation state of the area to be repaired, Fe(III)-polyphosphate complexing solution is added, wherein; When the area to be repaired is determined to be in a state of reaction inactivation, Fe(III)-polyphosphate complex solution is added to one or more areas adjacent to the area to be repaired. When the area to be repaired is not determined to be in a state of reaction inactivation, Fe(III)-polyphosphate complex solution is added to the area to be repaired.

3. The loess remediation method based on carbonate buffering and polyphosphate-reinforced Fenton-like structure according to claim 2, characterized in that, In step S53, the trend of redox potential change being continuously decreasing is defined as the existence of several consecutive sampling times within the preset historical time period, and the redox potential value at each sampling time being lower than the redox potential value at the previous sampling time.

4. The loess remediation method based on carbonate buffering and reinforced with Fenton-like phosphorus according to claim 3, characterized in that, Step S54 includes: Step S541: Determine the set of all regions adjacent to the region to be repaired; Step S542: Traverse the set of adjacent regions and select regions in which the process pH value is greater than the second pH threshold and the redox potential value is greater than the second potential threshold to form a qualified set of adjacent regions. Step S543: Determine whether the set of qualified adjacent regions is an empty set; Step S544: If the set of qualified adjacent regions is not empty, then Fe(III)-polyphosphate complex solution is added to all regions in the set. If the set of qualified adjacent regions is empty, then Fe(III)-polyphosphate complex solution is added to the region to be repaired.

5. The loess remediation method based on carbonate buffering and polyphosphate-reinforced Fenton-like structure according to claim 4, characterized in that, In step S544, the actual amount of Fe(III)-polyphosphate complex solution added is determined based on the process parameter state of the added area and the corresponding peroxide addition mode. Specifically, the basic addition amount is calculated based on the difference between the process pH value of the area to be repaired and the first pH threshold. The basic addition amount is then corrected based on the addition mode of the area to be repaired to obtain the actual addition amount.

6. The loess remediation method based on carbonate buffering and polyphosphate-reinforced Fenton-like structure according to claim 1, characterized in that, Step S2 includes: Step S21: Based on the comparison results between the repair response index of each area of ​​the loess site to be repaired and the preset repair response index threshold, each area is divided into a high RRI area and a low RRI area. Step S22: Calculate the average repair response index based on the repair response index of all the high RRI regions; Step S23: Determine the theoretical number of batches to be added based on the average repair response index; Step S24: Correct the theoretical number of dosing batches based on the initial pH value of each low RRI zone, and determine the actual number of dosing batches for each low RRI zone corresponding to the batch dosing mode.

7. The loess remediation method based on carbonate buffering and polyphosphate-reinforced Fenton-like structure according to claim 1, characterized in that, Polyphosphates are one or more of the following: pyrophosphate, tripolyphosphate, trimetaphosphate, tetrapolyphosphate, or hexametaphosphate.

8. The loess remediation method based on carbonate buffering and polyphosphate-reinforced Fenton-like structure according to claim 7, characterized in that, The concentration of the polyphosphate solution is 5 mmol / L to 100 mmol / L; the concentration of the Fe(III) solution is 5 mmol / L to 50 mmol / L.

9. The loess remediation method based on carbonate buffering and polyphosphate-reinforced Fenton-like structure according to claim 8, characterized in that, The molar ratio of Fe(III) to polyphosphate is 1:0.5 to 1:

2.

10. The loess remediation method based on carbonate buffering and polyphosphate-reinforced Fenton-like structure according to claim 9, characterized in that, The peroxide is at least one of hydrogen peroxide, persulfate, or perdisulfate; the concentration of the peroxide is in the range of 50 mmol / L to 500 mmol / L, and the molar ratio of Fe(III) to the peroxide is 1:5 to 1:50.

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