Test system and method for removing non-aqueous phase pollutants by using Cyrene reagent

Abstract

The invention discloses a test system and method for removing non-aqueous phase pollutants by using a Cyre reagent, and belongs to the technical field of non-aqueous phase pollutant remediation, the test system comprises a micro-fluidic chip, the micro-fluidic chip is arranged on an objective table of an optical microscope, a CCD camera is arranged above an eyepiece of the optical microscope, and the CCD camera is arranged on the objective table of the optical microscope. A lens of the CCD camera is aligned with the micro-fluidic chip through an eyepiece of the optical microscope; and the CCD camera is connected with a data acquisition system for acquiring pictures shot by the CCD camera. Microcosmic visualization is achieved, the displacement remediation effect of a displacement remediation agent based on Cyrene as a novel soil displacement remediation treatment reagent can be visually observed, and the permeability difference is provided through arrangement of a high-permeability area and a low-permeability area in the micro-fluidic chip; and the removal effect of the Cyrene-based displacement repair agent on non-aqueous phase pollutants in a low-permeability area can be better tested.

Description

Technical Field

[0001] The invention belongs to the technical field of non-aqueous phase pollutant remediation, and specifically relates to a test system and method for removing non-aqueous phase pollutants using a Cyrene reagent. Background Art

[0002] Soil and groundwater quality is often compromised by non-aqueous pollutants, which come from a variety of sources, including oil spills, pipeline ruptures, underground tank leaks, and industrial emissions. Non-aqueous pollutants include benzene, toluene, xylene, ethylbenzene, and polycyclic aromatic hydrocarbons, which exhibit "triple-causing" effects, namely carcinogenicity, teratogenicity, and mutagenicity, posing serious risks to animal, plant, and human health.

[0003] At present, there are various methods for treating non-aqueous phase pollutants in groundwater, including traditional pumping treatment, bioremediation and surfactant-enhanced aquifer remediation technology. Among them, the pumping treatment method is to extract the contaminated groundwater, which has low efficiency and high maintenance cost. Bioremediation relies heavily on microbial degradation and is easily limited by microbial adaptability and long remediation cycle. Surfactant-enhanced aquifer remediation technology is to displace non-aqueous phase pollutants in contaminated water by inputting active agents. It can remove non-aqueous phase pollutants adsorbed on the soil surface and has high removal efficiency for non-aqueous phase pollutants. However, these active agents are expensive and may cause secondary pollution, which limits their wide application.

[0004] Based on the problem that surfactants in existing surfactant-enhanced aquifer remediation technologies may cause secondary pollution, this application considers applying Cyrene to the displacement and remediation of non-aqueous phase pollutants in groundwater systems. The Chinese name of Cyrene is dihydrolevorotatory glucosone, which is a green bio-derived solvent that can be obtained from materials such as crop straw, waste paper and sawdust through cellulose pyrolysis. It is relatively non-toxic and completely biodegradable. When a small amount of water is added to Cyrene, the resulting diol-form derivatives can significantly increase the solubility of hydrophobic compounds. Cyrene will not cause secondary pollution during the displacement and remediation of non-aqueous phase pollutants in groundwater systems, and is not easily affected by adsorption and distribution losses. It has great potential to improve the displacement and removal of non-aqueous phase pollutants in heterogeneous porous media.

[0005] In order to evaluate the displacement and removal effect of Cyrene on non-aqueous phase pollutants over time, the present application proposes a test system and method for removing non-aqueous phase pollutants with Cyrene reagent. Summary of the invention

[0006] The purpose of the present invention is to overcome the above-mentioned deficiencies of the prior art and provide a test system for removing non-aqueous phase pollutants using Cyrene reagent.

[0007] To achieve the above object, the present invention adopts the following technical solution:

[0008] A test system for removing non-aqueous phase pollutants using Cyrene reagent, comprising a microfluidic chip with a pore structure for simulating the soil environment where groundwater is located;

[0009] The inlet of the microfluidic chip can be connected to the outlet ends of multiple micro-injectors on a micro-injection pump through a pipeline, and the outlet of the microfluidic chip is connected to a waste liquid bottle through a pipeline;

[0010] The microfluidic chip is placed on a stage of an optical microscope, and a light source is arranged on the stage of the optical microscope;

[0011] A CCD camera is arranged above the eyepiece of the optical microscope, and a lens of the CCD camera is aimed at the microfluidic chip through the eyepiece of the optical microscope;

[0012] The CCD camera is connected to a data acquisition system used to acquire pictures taken by the CCD camera.

[0013] Preferably, the middle area inside the microfluidic chip is a mainstream area with a rectangular structure, and the left and right sides of the mainstream area are an inlet area and an outlet area with a symmetrical isosceles triangle structure;

[0014] The main flow area, inlet area and outlet area all present pore structures;

[0015] The inlet area is connected to the inlet at a point away from the apex of the main flow area;

[0016] The outlet zone is connected to the outlet at a point away from the apex of the main flow zone.

[0017] Preferably, the microfluidic chip comprises a base with an open top box-shaped structure, a plurality of cylinders for simulating soil particles are arranged on the inner bottom surface of the base, a blocking top plate is fixedly arranged on the top surface of the base, and the top surface of the cylinder is sealed against the blocking top plate;

[0018] The base, the cylinder and the blocking top plate are all made of PDMS and have a transparent structure.

[0019] Preferably, the inlet area and the outlet area present a uniform pore structure, and the porosity of the inlet area and the outlet area is consistent.

[0020] Preferably, the mainstream area includes a high permeability area and a low permeability area distributed in the up-down direction, and the high permeability area and the low permeability area are both rectangular in structure;

[0021] The high permeability zone and the low permeability zone both present a uniform pore structure, the porosity of the high permeability zone is greater than the porosity of the low permeability zone, and the porosity of the high permeability zone is consistent with the porosity of the inlet zone;

[0022] The ratio of the width L1 of the hypertonic zone along the up-down direction to the width L of the mainstream zone along the up-down direction ranges from 0 to 1.

[0023] The invention also provides a test method for removing non-aqueous phase pollutants by using Cyrene reagent.

[0024] A test method for removing non-aqueous phase pollutants using a Cyrene reagent is implemented based on a test system for removing non-aqueous phase pollutants using a Cyrene reagent, and includes the following steps:

[0025] Step 1, placing the microfluidic chip in an ultrasonic cleaner for ultrasonic cleaning;

[0026] Step 2, placing the microfluidic chip in a vacuum drying oven for drying;

[0027] Step 3, preparing the mineral oil and crude oil into non-aqueous phase pollutants according to the ratio required by the test;

[0028] Step 4, prepare a displacement repair agent by mixing Cyrene and water in the proportion required by the test;

[0029] Step 5, placing the microfluidic chip on the stage of an optical microscope, selecting a suitable optical microscope objective lens, making the field of view under the optical microscope eyepiece the microfluidic chip, and adjusting the focal length of the CCD camera to focus on the microfluidic chip;

[0030] Connect the outlet of the microfluidic chip to the waste liquid bottle through a pipe;

[0031] Step 6, injecting non-aqueous phase pollutants into the microfluidic chip through the first microinjector on the microinjection pump, and stopping the injection when the microfluidic chip is visually filled with non-aqueous phase pollutants;

[0032] Controlling the CCD camera to take an initial picture of the microfluidic chip filled with non-aqueous phase pollutants;

[0033] Step 7: injecting the displacing repair agent into the microfluidic chip at a constant flow rate through the second microinjector on the microinjection pump;

[0034] Control the CCD camera to take several repair test pictures of the microfluidic chip injected with the repair agent, and transmit them to the data acquisition system;

[0035] Step 8: Calculate the residual oil saturation of each repair test image at the corresponding shooting time based on the captured images.

[0036] Preferably, step 8 includes the following sub-steps:

[0037] Step 81, numbering the initial image and the restoration test image from small to large in the order of shooting time to obtain the number N of images;

[0038] Step 82, using Python to read the initial image, obtain the position coordinates of the four vertices of the rectangular area of ​​the mainstream area and save them;

[0039] Step 83, using Python to process the initial image in HSV format, obtain the H value interval of the hue H, the S value interval of the saturation S, and the V value interval of the lightness V in the pixel points in the mainstream area and save them;

[0040] Step 84, obtaining the grayscale value of each pixel in the mainstream area of ​​the initial image, and taking the difference between 255 and the grayscale value of the pixel as the oil concentration value at the corresponding pixel;

[0041] The sum of the oil concentration values ​​at each pixel in the mainstream area of ​​the initial image is taken as the initial oil concentration value α;

[0042] Step 85, using the PIL library in Python to read all the repair test images, cropping the images according to the four vertex coordinates in step 82, and retaining the rectangular area surrounded by the four vertex coordinates;

[0043] Step 86, performing HSV format processing on all cropped restoration test images;

[0044] Step 87, processing all the cropped restoration test images in ascending order of digital numbers to obtain the residual oil saturation corresponding to each image;

[0045] Step 88: The calculation of the residual oil saturation of each repair test image at the corresponding shooting time is completed.

[0046] Preferably, the step 83 includes the following sub-steps:

[0047] Step 831, using the PIL library in Python to read the initial image, and processing the initial image in HSV format;

[0048] Step 832, traverse all pixel points in the mainstream area of ​​the initial image according to the position coordinates of the four vertices of the rectangular area of ​​the mainstream area of ​​the initial image;

[0049] Step 833, sort the hue H, saturation S, and brightness V of all pixels in the mainstream area of ​​the initial image from large to small, and obtain three groups of value intervals, namely H value interval, S value interval, and V value interval, and save the three groups of value intervals.

[0050] Preferably, the step 87 includes the following sub-steps:

[0051] Step 871: define i as the number of processed pictures, define j as the digital code of the last processed picture, let i=1, j=1;

[0052] Step 872: If i<N, proceed to step 873;

[0053] If i=N, proceed to step 88;

[0054] Step 873: Let j=j+1, and define the picture with digital code j as the current picture;

[0055] Traverse all pixel points of the current image according to the image size of the current image, and select pixel points whose hue H is in the H value interval, saturation S is in the S value interval, and lightness V is in the V value interval as residual oil pixel points;

[0056] Convert the current image into a grayscale image, and set the area where the pixels other than the residual oil pixels are located to be transparent;

[0057] Obtain the grayscale value of each pixel in the current image, and take the difference between 255 and the grayscale value of the pixel as the oil concentration value at the corresponding pixel;

[0058] The sum of the oil concentration values ​​at each pixel point in the current image is taken as the current image oil concentration value αj;

[0059] Calculate the residual oil saturation η in the current picture j ;

[0060]

[0061] The residual oil saturation η in the current picture j Output;

[0062] Let i=i+1 and go to step 872.

[0063] The beneficial effects of the present invention are:

[0064] (1) The present invention realizes microscopic visualization, and can directly observe the displacement and repair effect of the Cyrene-based displacement and repair agent as a new type of soil displacement and repair treatment agent. The microfluidic chip provides permeability differences through the setting of high permeability zones and low permeability zones, which can better test the removal effect of the Cyrene-based displacement and repair agent on non-aqueous phase pollutants in the low permeability zone.

[0065] (2) Since the Cyrene-based displacement and repair agent is accompanied by dissolution during the displacement and repair, the conventional microfluidic image processing based on pixel statistical methods is not applicable to the experimental results of this application. Therefore, this application is based on the Python program, and the difference between 255 and the gray value of the pixel is used as the oil concentration value at the corresponding pixel point, which realizes quantitative analysis. By calculating the residual oil saturation at each moment, it is used to evaluate the displacement and removal effect of the Cyrene-based displacement and repair agent on non-aqueous phase pollutants over time. BRIEF DESCRIPTION OF THE DRAWINGS

[0066] The drawings in the specification, which constitute a part of the present application, are used to provide further understanding of the present application. The illustrative embodiments of the present application and their descriptions are used to explain the present application and do not constitute improper limitations on the present application.

[0067] Figure 1 It is a connection schematic diagram of the test system for removing non-aqueous phase pollutants using the Cyrene reagent of the present invention;

[0068] Figure 2 It is a schematic diagram of the structure of the microfluidic chip in the present invention;

[0069] Figure 3 is a grayscale image of the initial image in Embodiment 3 of the present invention;

[0070] Figure 4 is a cropped grayscale image of the repair test image numbered 5 in Example 3 of the present invention;

[0071] Figure 5 is a cropped grayscale image of the repair test image numbered 9 in Example 3 of the present invention;

[0072] Figure 6 is a cropped grayscale image of the repair test image numbered 10 in Example 3 of the present invention;

[0073] in:

[0074] 1-microfluidic chip, 101-base, 102-column, 103-inlet, 104-outlet, 105-mainstream area, 1051-hypertonic area, 1052-hypotonic area, 106-inlet area, 107-outlet area;

[0075] 2-micro-injection pump, 3-micro-injector, 4-waste liquid bottle, 5-optical microscope, 6-CCD camera, 7-data acquisition system. DETAILED DESCRIPTION

[0076] It should be noted that the following detailed descriptions are illustrative and are intended to provide further explanation of the present application. Unless otherwise specified, all technical and scientific terms used herein have the same meanings as those commonly understood by those skilled in the art to which the present application belongs.

[0077] It should be noted that the terms used herein are only for describing specific embodiments and are not intended to limit the exemplary embodiments according to the present application. As used herein, unless the context clearly indicates otherwise, the singular form is also intended to include the plural form. In addition, it should be understood that when the terms "comprise" and / or "include" are used in this specification, it indicates the presence of features, steps, operations, devices, components and / or combinations thereof.

[0078] In the present invention, the directions or positional relationships indicated by terms such as "upper", "lower", "bottom", "top", etc. are based on the directions or positional relationships shown in the accompanying drawings. They are relational words determined only for the convenience of describing the structural relationships of the various parts or elements of the present invention. They do not specifically refer to any part or element in the present invention and cannot be understood as limitations on the present invention.

[0079] In the present invention, terms such as "connected" and "connection" should be understood in a broad sense, indicating that the connection can be fixed, integral or detachable; it can be directly connected or indirectly connected through an intermediate medium. Relevant scientific research or technical personnel in this field can determine the specific meaning of the above terms in the present invention according to specific circumstances, and they should not be understood as limiting the present invention.

[0080] The present invention is further described below in conjunction with the accompanying drawings and embodiments.

[0081] Embodiment 1:

[0082] like Figure 1 As shown, a test system for removing non-aqueous phase pollutants using Cyrene reagent includes a microfluidic chip 1 with a pore structure for simulating the soil environment where groundwater is located;

[0083] The inlet 103 of the microfluidic chip 1 can be connected to the outlet ends of the multiple micro-injectors 3 on the micro-injection pump 2 through a pipeline, and the outlet 104 of the microfluidic chip 1 is connected to the waste liquid bottle 4 through a pipeline;

[0084] The microfluidic chip 1 is placed on the stage of an optical microscope 5, and a light source is provided on the stage of the optical microscope 5;

[0085] A CCD camera 6 is arranged above the eyepiece of the optical microscope 5, and the lens of the CCD camera 6 is aimed at the microfluidic chip 1 through the eyepiece of the optical microscope 5;

[0086] The CCD camera 6 is connected to a data acquisition system 7 for acquiring pictures taken by the CCD camera 6 .

[0087] Preferably, Figure 2 As shown, the middle area inside the microfluidic chip 1 is a mainstream area 105 with a rectangular structure, and the left and right sides of the mainstream area 105 are an inlet area 106 and an outlet area 107 with a symmetrical isosceles triangle structure;

[0088] The main flow area 105, the inlet area 106, and the outlet area 107 are all porous structures;

[0089] The inlet area 106 is connected to the inlet 103 at a point away from the main flow area 105;

[0090] The outlet area 107 is connected to the outlet 104 at a point away from the apex of the mainstream area 105 .

[0091] Preferably, the microfluidic chip 1 comprises a base 101 with an open top box-shaped structure, a plurality of cylinders 102 for simulating soil particles are arranged on the inner bottom surface of the base 101, a blocking top plate is fixedly arranged on the top surface of the base 101, and the top surface of the cylinder 102 is sealed against the blocking top plate;

[0092] The base 101, the cylinder 102, and the sealing top plate are all made of PDMS and have a transparent structure.

[0093] Preferably, the inlet area 106 and the outlet area 107 present a uniform pore structure, and the porosity of the inlet area 106 and the outlet area 107 is consistent. The porosity of the inlet area 106 refers to the ratio of the volume of pores in the inlet area 106 that are interconnected and allow fluid to flow to the total volume of the inlet area 106, and the porosity of the outlet area 107 refers to the ratio of the volume of pores in the outlet area 107 that are interconnected and allow fluid to flow to the total volume of the outlet area.

[0094] Preferably, the mainstream area 105 includes a high permeability area 1051 and a low permeability area 1052 distributed in the up-down direction, and the high permeability area 1051 and the low permeability area 1052 are both rectangular structures;

[0095] The hypertonic zone 1051 and the hypotonic zone 1052 both present a uniform pore structure, the porosity of the hypertonic zone 1051 is greater than the porosity of the hypotonic zone 1052, and the porosity of the hypertonic zone 1051 is consistent with the porosity of the inlet zone 106; the porosity of the hypertonic zone 1051 refers to the ratio of the volume of pores interconnected in the hypertonic zone 1051 that allow fluid to flow to the total volume of the hypertonic zone 1051, and the porosity of the hypotonic zone 1052 refers to the ratio of the volume of pores interconnected in the hypotonic zone 1052 that allow fluid to flow to the total volume of the hypotonic zone 1052;

[0096] The ratio of the width L1 of the hyperosmotic zone 1051 along the up-down direction to the width L of the mainstream zone 105 along the up-down direction ranges from 0 to 1.

[0097] Embodiment 2:

[0098] A test method for removing non-aqueous phase pollutants with Cyrene reagent is implemented based on the test system for removing non-aqueous phase pollutants with Cyrene reagent in Example 1, comprising the following steps:

[0099] Step 1, placing the microfluidic chip 1 in an ultrasonic cleaner for ultrasonic cleaning, specifically performing ultrasonic cleaning for 10 minutes;

[0100] Step 2, placing the microfluidic chip 1 in a vacuum drying oven for drying, specifically drying in a vacuum drying oven at 100° C. for 10 minutes;

[0101] Step 3, preparing the mineral oil and crude oil into non-aqueous phase pollutants according to the ratio required by the test;

[0102] Step 4, prepare a displacement repair agent by mixing Cyrene and water in the proportion required by the test;

[0103] Step 5, placing the microfluidic chip 1 on the stage of the optical microscope 5, selecting a suitable objective lens of the optical microscope 5, making the field of view under the eyepiece of the optical microscope 5 the microfluidic chip 1, and adjusting the focal length of the CCD camera 6 to focus on the microfluidic chip 1;

[0104] Connect the outlet 104 of the microfluidic chip 1 to the waste liquid bottle 4 through a pipeline;

[0105] Step 6, injecting non-aqueous phase pollutants into the microfluidic chip 1 through the first microinjector 3 on the microinjection pump 2, and stopping the injection when the microfluidic chip 1 is visually filled with non-aqueous phase pollutants;

[0106] Controlling the CCD camera 6 to take an initial picture of the microfluidic chip 1 filled with non-aqueous phase pollutants;

[0107] Step 7: injecting the displacing repair agent into the microfluidic chip 1 at a constant flow rate through the second microinjector 3 on the microinjection pump 2, wherein the injection time of the displacing repair agent is one hour;

[0108] Control the CCD camera 6 to take a number of repair test pictures of the microfluidic chip 1 injected with the repair agent, and transmit them to the data acquisition system 7; specifically, use the CCD camera 6 to regularly take images of the microfluidic chip 1, maintain a shooting interval of 10 seconds, the CCD camera 6 is connected to the data acquisition system 7, and each image is recorded through the Image-View software;

[0109] Step 8: Calculate the residual oil saturation of each repair test image at the corresponding shooting time based on the captured images.

[0110] Preferably, step 8 includes the following sub-steps:

[0111] Step 81, numbering the initial image and the restoration test image from small to large in the order of shooting time to obtain the number N of images;

[0112] Step 82, using Python to read the initial image, obtain the position coordinates of the four vertices of the rectangular area of ​​the mainstream area 105 and save them. Specifically, by clicking the four vertices of the rectangular area of ​​the mainstream area 105, the position coordinates of the four vertices of the mainstream area 105 can be obtained;

[0113] In step 82 of the present application, the position coordinates of the four vertices of the mainstream area 105 of the initial image are obtained to determine the position of the mainstream area 105. Since the position of the microfluidic chip 1 remains unchanged when a group of experiments are performed, the position of the mainstream area 105 in the initial image and all subsequent experimental repair images will not change. By determining the position of the mainstream area 105 in the initial image, the position of the mainstream area 105 corresponding to all experimental repair images corresponding to the group of experiments can be determined; that is, it is only necessary to manually determine the position of the mainstream area in one image, and according to the saved four vertex position coordinates, the position of the mainstream area 105 of the remaining images can be identified and cropped.

[0114] Step 83, using Python to process the initial image in HSV format, obtain the H value interval of the hue H, the S value interval of the saturation S, and the V value interval of the lightness V in the pixel points in the mainstream area 105 and save them;

[0115] Specifically, the step 83 includes the following sub-steps:

[0116] Step 831, using the PIL library in Python to read the initial image, and processing the initial image in HSV format;

[0117] Step 832, traversing all pixel points in the mainstream area 105 of the initial image according to the position coordinates of the four vertices of the rectangular area of ​​the mainstream area 105 of the initial image;

[0118] Step 833, sorting the hue H, saturation S, and brightness V of all pixels in the mainstream area 105 of the initial image from large to small, obtaining three groups of value intervals, namely, the H value interval, the S value interval, and the V value interval, and saving the three groups of value intervals;

[0119] Step 84, converting the mainstream area 105 of the initial image into a grayscale image, obtaining the grayscale value of each pixel in the mainstream area 105 of the initial image, and taking the difference between 255 and the grayscale value of the pixel as the oil concentration value at the corresponding pixel;

[0120] The sum of the oil concentration values ​​at each pixel point in the mainstream area 105 of the initial image is taken as the initial oil concentration value α;

[0121] Step 85, using the PIL library in Python to read all the repair test images, cropping the images according to the four vertex coordinates in step 82, and retaining the rectangular area surrounded by the four vertex coordinates;

[0122] Step 86, performing HSV format processing on all cropped restoration test images;

[0123] Step 87, processing all the cropped restoration test images in ascending order of digital numbers to obtain the residual oil saturation corresponding to each image;

[0124] Specifically, the step 87 includes the following sub-steps:

[0125] Step 871: define i as the number of processed pictures, define j as the digital code of the last processed picture, let i=1, j=1;

[0126] Step 872: If i<N, proceed to step 873;

[0127] If i=N, proceed to step 88;

[0128] Step 873: Let j=j+1, and define the picture with digital code j as the current picture;

[0129] Traverse all pixel points of the current image according to the image size of the current image, and select pixel points whose hue H is in the H value interval, saturation S is in the S value interval, and lightness V is in the V value interval as residual oil pixel points;

[0130] Convert the current image into a grayscale image, and set the area where the pixels other than the residual oil pixels are located to be transparent;

[0131] Obtain the grayscale value of each pixel in the current image, and take the difference between 255 and the grayscale value of the pixel as the oil concentration value at the corresponding pixel;

[0132] The sum of the oil concentration values ​​at each pixel point in the current image is taken as the current image oil concentration value αj;

[0133] Calculate the residual oil saturation η in the current picture j ;

[0134]

[0135] The residual oil saturation η in the current picture j Output;

[0136] Let i=i+1, and proceed to step 872;

[0137] Step 88: The calculation of the residual oil saturation of each repair test image at the corresponding shooting time is completed.

[0138] In the grayscale image, the larger the grayscale value, the brighter and whiter the pixel, and the smaller the grayscale value, the darker and blacker the pixel. In the captured image, the darker area represents a higher oil concentration, and the brighter area represents a lower oil concentration. Therefore, the grayscale value is inversely proportional to the actual oil concentration. Therefore, this application uses the difference between 255 and the grayscale value of the pixel as the oil concentration value at the corresponding pixel to achieve quantitative analysis.

[0139] The present invention realizes microscopic visualization, and can directly observe the displacement and repair effect of the Cyrene-based displacement and repair agent as a new type of soil displacement and repair treatment agent. The microfluidic chip 1 provides a permeability difference through the setting of the high permeability zone 1051 and the low permeability zone 1052, which can better test the removal effect of the Cyrene-based displacement and repair agent on non-aqueous phase pollutants in the low permeability area.

[0140] Since the Cyrene-based displacement and repair agent is accompanied by dissolution behavior during displacement and repair, the conventional microfluidic image processing based on pixel statistical methods is not applicable to the experimental results of this application. Therefore, this application is based on the Python program, and the difference between 255 and the pixel grayscale value is used as the oil concentration value at the corresponding pixel point to achieve quantitative analysis. By calculating the residual oil saturation at each moment, it is used to evaluate the displacement and removal effect of the Cyrene-based displacement and repair agent on non-aqueous phase pollutants over time.

[0141] Embodiment 3:

[0142] The test method in Example 2 was used for the test, wherein the ratio of the width L1 of the hypertonic zone 1051 along the up-down direction to the width L of the mainstream zone 105 along the up-down direction was 0.5; the diameter of the cylinder 102 in the hypertonic zone 1051 was 0.4 mm, and the distance between the centers of the top surfaces of adjacent cylinders 102 in the hypertonic zone 1051 was 0.5 mm; the diameter of the cylinder 102 in the hypotonic zone 1052 was 0.1 mm, and the distance between the centers of the top surfaces of adjacent cylinders 102 in the hypotonic zone 1052 was 0.105 mm; the porosity of the hypertonic zone 1051 was 0.342, and the porosity of the hypotonic zone 1052 was 0.119.

[0143] The mineral oil used in the non-aqueous phase pollutant is Mobil Glygoyle 100, and the mineral oil and crude oil are mixed in a volume ratio of 8:1.

[0144] Cyrene and water are mixed in a mass ratio of 1:2 to form a displacement repair agent.

[0145] The displacement repair agent is injected into the microfluidic chip 1 at a constant flow rate of 50 μL / hour through the second microinjector 3 on the microinjection pump 2 .

[0146] CCD camera 6 takes the initial picture and 10 restoration test pictures, so N is 11 and the digital number of the initial picture is 1.

[0147] After calculation, the initial oil concentration value α is 503607722. The residual oil saturation of each repair test picture at the corresponding shooting time is obtained, as shown in Table 1 below.

[0148] Table 1 Residual oil saturation of each repair test image at the time of shooting

[0149] j 2 3 4 5 6 αj 479073774 391181419 343078086 311687100 284516577 <![CDATA[η j ]]> 95.13％ 77.68％ 68.12％ 61.89％ 56.50％ j 7 8 9 10 11 αj 263976382 246651619 233452893 218465760 92505706 <![CDATA[η j ]]> 52.42％ 48.98％ 46.36％ 43.38％ 18.37％

[0150] The grayscale image of the initial mainstream image 105 is as follows Figure 3 As shown in the figure, the cropped grayscale image of the repair test image numbered 5 is as follows Figure 4 As shown in the figure, the cropped grayscale image of the repair test image numbered 9 is as follows Figure 5 As shown in the figure, the cropped grayscale image of the repair test image numbered 10 is as follows Figure 6 shown.

[0151] Although the above describes the specific implementation mode of the present invention in conjunction with the accompanying drawings, it is not a limitation of the present invention. Those skilled in the art should understand that various modifications or variations that can be made by those skilled in the art on the basis of the technical solution of the present invention without creative work are still within the protection scope of the present invention.

Claims

1. A test system for removing non-aqueous phase pollutants using Cyrene reagent, characterized in that: It includes a microfluidic chip with a pore structure used to simulate the soil environment where groundwater is located; The inlet of the microfluidic chip can be connected to the outlet ends of multiple micro-injectors on a micro-injection pump through a pipeline, and the outlet of the microfluidic chip is connected to a waste liquid bottle through a pipeline; The microfluidic chip is placed on a stage of an optical microscope, and a light source is arranged on the stage of the optical microscope; A CCD camera is arranged above the eyepiece of the optical microscope, and a lens of the CCD camera is aimed at the microfluidic chip through the eyepiece of the optical microscope; The CCD camera is connected to a data acquisition system used to acquire pictures taken by the CCD camera.

2. The test system for removing non-aqueous phase pollutants with Cyrene reagent as claimed in claim 1, characterized in that: The middle area inside the microfluidic chip is a mainstream area with a rectangular structure, and the left and right sides of the mainstream area are an inlet area and an outlet area with a symmetrical isosceles triangle structure; The main flow area, inlet area and outlet area all present pore structures; The inlet area is connected to the inlet at a point away from the apex of the main flow area; The outlet zone is connected to the outlet at a point away from the apex of the main flow zone.

3. The test system for removing non-aqueous phase pollutants using Cyrene reagent as claimed in claim 1, characterized in that: The microfluidic chip comprises a base with an open top box-shaped structure, a plurality of cylinders for simulating soil particles are arranged on the inner bottom surface of the base, a blocking top plate is fixedly arranged on the top surface of the base, and the top surface of the cylinder is sealed against the blocking top plate; The base, the cylinder and the blocking top plate are all made of PDMS and have a transparent structure.

4. The test system for removing non-aqueous phase pollutants using Cyrene reagent as claimed in claim 2, characterized in that: The inlet area and the outlet area present a uniform pore structure, and the porosity of the inlet area and the outlet area is consistent.

5. The test system for removing non-aqueous phase pollutants with Cyrene reagent as claimed in claim 4, characterized in that: The mainstream area includes a high permeability area and a low permeability area distributed in the up-down direction, and the high permeability area and the low permeability area are both rectangular in structure; The high permeability zone and the low permeability zone both present a uniform pore structure, the porosity of the high permeability zone is greater than the porosity of the low permeability zone, and the porosity of the high permeability zone is consistent with the porosity of the inlet zone; The ratio of the width L1 of the hypertonic zone along the up-down direction to the width L of the mainstream zone along the up-down direction ranges from 0 to 1.

6. A test method for removing non-aqueous phase pollutants using Cyrene reagent, which is implemented based on the test system for removing non-aqueous phase pollutants using Cyrene reagent as claimed in any one of claims 1 to 5, characterized in that: The following steps are involved: Step 1, placing the microfluidic chip in an ultrasonic cleaner for ultrasonic cleaning; Step 2, placing the microfluidic chip in a vacuum drying oven for drying; Step 3, preparing the mineral oil and crude oil into non-aqueous phase pollutants according to the ratio required by the test; Step 4, prepare a displacement repair agent by mixing Cyrene and water in the proportion required by the test; Step 5, placing the microfluidic chip on the stage of an optical microscope, selecting a suitable optical microscope objective lens, making the field of view under the optical microscope eyepiece the microfluidic chip, and adjusting the focal length of the CCD camera to focus on the microfluidic chip; Connect the outlet of the microfluidic chip to the waste liquid bottle through a pipe; Step 6, injecting non-aqueous phase pollutants into the microfluidic chip through the first microinjector on the microinjection pump, and stopping the injection when the microfluidic chip is visually filled with non-aqueous phase pollutants; Controlling the CCD camera to take an initial picture of the microfluidic chip filled with non-aqueous phase pollutants; Step 7: injecting the displacing repair agent into the microfluidic chip at a constant flow rate through the second microinjector on the microinjection pump; Control the CCD camera to take several repair test pictures of the microfluidic chip injected with the repair agent, and transmit them to the data acquisition system; Step 8: Calculate the residual oil saturation of each repair test image at the corresponding shooting time based on the captured images.

7. The test method for removing non-aqueous phase pollutants by Cyrene reagent as claimed in claim 6, characterized in that: The step 8 comprises the following sub-steps: Step 81, numbering the initial image and the restoration test image from small to large in the order of shooting time to obtain the number N of images; Step 82, using Python to read the initial image, obtain the position coordinates of the four vertices of the rectangular area of ​​the mainstream area and save them; Step 83, using Python to process the initial image in HSV format, obtain the H value interval of the hue H, the S value interval of the saturation S, and the V value interval of the lightness V in the pixel points in the mainstream area and save them; Step 84, obtaining the grayscale value of each pixel in the mainstream area of ​​the initial image, and taking the difference between 255 and the grayscale value of the pixel as the oil concentration value at the corresponding pixel; The sum of the oil concentration values ​​at each pixel in the mainstream area of ​​the initial image is taken as the initial oil concentration value α; Step 85, using the PIL library in Python to read all the repair test images, cropping the images according to the four vertex coordinates in step 82, and retaining the rectangular area surrounded by the four vertex coordinates; Step 86, performing HSV format processing on all cropped restoration test images; Step 87, processing all the cropped restoration test images in ascending order of digital numbers to obtain the residual oil saturation corresponding to each image; Step 88: The calculation of the residual oil saturation of each repair test image at the corresponding shooting time is completed.

8. The test method for removing non-aqueous phase pollutants by Cyrene reagent as claimed in claim 7, characterized in that: The step 83 includes the following sub-steps: Step 831, using the PIL library in Python to read the initial image, and processing the initial image in HSV format; Step 832, traverse all pixel points in the mainstream area of ​​the initial image according to the position coordinates of the four vertices of the rectangular area of ​​the mainstream area of ​​the initial image; Step 833, sort the hue H, saturation S, and brightness V of all pixels in the mainstream area of ​​the initial image from large to small, and obtain three groups of value intervals, namely H value interval, S value interval, and V value interval, and save the three groups of value intervals.

9. The test method for removing non-aqueous phase pollutants by Cyrene reagent as claimed in claim 7, characterized in that: The step 87 includes the following sub-steps: Step 871: define i as the number of processed pictures, define j as the digital code of the last processed picture, let i=1, j=1; Step 872: If i<N, proceed to step 873; If i=N, proceed to step 88; Step 873: Let j=j+1, and define the picture with digital code j as the current picture; Traverse all pixel points of the current image according to the image size of the current image, and select pixel points whose hue H is in the H value interval, saturation S is in the S value interval, and lightness V is in the V value interval as residual oil pixel points; Convert the current image into a grayscale image, and set the area where the pixels other than the residual oil pixels are located to be transparent; Obtain the grayscale value of each pixel in the current image, and take the difference between 255 and the grayscale value of the pixel as the oil concentration value at the corresponding pixel; The sum of the oil concentration values ​​at each pixel in the current image is taken as the current image oil concentration value αj; the residual oil saturation η in the current image is calculated j ; The residual oil saturation η in the current picture j Output; Let i=i+1 and go to step 872.

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