CN114878528A - Method for quickly tracing surface water surface floating oil based on three-dimensional fluorescence spectroscopy - Google Patents
Method for quickly tracing surface water surface floating oil based on three-dimensional fluorescence spectroscopy Download PDFInfo
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- G01N21/62—Systems in which the material investigated is excited whereby it emits light or causes a change in wavelength of the incident light
- G01N21/63—Systems in which the material investigated is excited whereby it emits light or causes a change in wavelength of the incident light optically excited
- G01N21/64—Fluorescence; Phosphorescence
- G01N21/6428—Measuring fluorescence of fluorescent products of reactions or of fluorochrome labelled reactive substances, e.g. measuring quenching effects, using measuring "optrodes"
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Abstract
The invention discloses a method for quickly tracing surface water floating oil based on a three-dimensional fluorescence spectroscopy, which is characterized by comprising the steps of preparing a plurality of mixed oil solutions according to different concentration proportions to form a correction sample set, measuring the three-dimensional fluorescence spectrum of the correction sample set, analyzing three-dimensional fluorescence data by adopting a parallel factor algorithm to obtain the characteristic fluorescence peaks of several oils and establishing corresponding identification models; the method has the advantages of realizing rapid tracing of the surface water floating oil, having simple operation, low cost, safety, no pollution, strong practical applicability and no interference of other substances in water, and providing technical and data support for controlling the source of the surface water oil pollution.
Description
Technical Field
The invention relates to a method for quickly tracing surface water surface floating oil, in particular to a method for quickly tracing surface water surface floating oil based on a three-dimensional fluorescence spectroscopy.
Background
Oil enters the water environment through different ways and causes oil pollution, and the oil pollution is pollution with large amount, wide distribution and serious harm. It can be divided into: natural sources (about 8%) and human active sources (about 92%). For surface water, gasoline, diesel oil and engine oil leakage generated in the automobile industry, the mechanical industry, the construction site and the like, and oily wastewater discharge in the catering industry and the food processing industry are important sources of oil pollution. The discharge points of the oil pollutants are dispersed and hidden, and can enter the water body by other indirect modes, such as rainwater runoff and the like, so that the water environment is damaged. After the oil pollutants enter the water body, oil films with different thicknesses are formed on the water surface to isolate the water body from the atmosphere, so that dissolved oxygen in the water body is reduced, and further aquatic organisms are killed greatly. The oil film and oil drop can also be attached to fish gills to suffocate the fish or attached to plants to block photosynthesis and respiration of the plants. The nondegradable organic matters in the oil pollutants can be reserved in the water body for a long time, and are enriched in the animal body in modes of animal respiration, food chain transmission and the like, so that the nondegradable organic matters have toxic and harmful effects on aquatic organisms, and even enter the human body through the food chain to cause various diseases. Therefore, oil pollution of surface water is a realistic problem which needs to be solved urgently. The most obvious expression of oil pollution of surface water is that an oil film floats on the water surface, and in order to effectively control and treat the oil pollution of the surface water, the important prerequisites are to effectively extract the oil floating on the water surface and analyze and identify the oil pollutants in the oil floating on the water surface. The source and the proportion of oil pollutants in the floating oil on the water surface can be accurately and quickly identified, and the possibility that the waste water in the automobile industry, the mechanical industry, the catering industry and the like is discharged into surface water and potential oil leakage points can be speculated by using common oils such as gasoline, diesel oil, waste engine oil and vegetable oil as contribution factors, so that the source control can be performed on the waste water in a targeted manner, and the effective treatment can be performed.
At present, methods applied to identification of oil pollutants in water bodies include gas chromatography, gas chromatography-mass spectrometry, high performance liquid chromatography and the like, and the methods can be used for determining the content and distribution characteristics of various monomer hydrocarbons in the oil pollutants, but in practical application, the cost of using and maintaining an instrument is high, the sample pretreatment step is complicated, the loss is large, and the determination time is long. Another type of analysis method is to determine the total hydrocarbons in oil pollutants, including infrared spectroscopy, ultraviolet spectroscopy, etc., and roughly judge the type and source of the pollutants according to the overall characteristics of a certain type of compounds, and such methods have simple sample pretreatment and fast analysis speed, but have certain limitations in the analysis and identification of oil pollutants, such as being susceptible to the physical state of the sample and various oil additives. In addition, these methods are primarily focused on identification of the source of single oil contamination, and do not effectively identify the source and contribution ratio of multiple mixed oil contamination.
The three-dimensional fluorescence spectrometry is a method for performing semi-quantitative analysis on a substance by utilizing three-dimensional spectral information formed by different classes of compounds with different fluorescence responses according to excitation wavelength (Ex), emission wavelength (Em) and fluorescence intensity, and has the characteristics of simple instrument and equipment and operation, low cost, high analysis speed, high sensitivity, good selectivity, large information amount and the like. The three-dimensional fluorescence spectrum generally has a plurality of fluorescence areas and fluorescence peaks, the fluorescence peaks overlap to a certain degree, and the traditional peak value method and the traditional fluorescence area method cannot fundamentally solve the problem of fluorescence peak overlap, so that the deviation of an analysis result is caused. The parallel factor analysis (PARAFAC) is a three-dimensional array decomposition algorithm based on the trilinear decomposition theory and adopting the alternating least square principle to solve iteratively, and can split the original data of the three-dimensional fluorescence spectrum into different characteristic peaks so as to perform spectrum decomposition. At present, three-dimensional fluorescence spectroscopy combined with parallel factor analysis (PARAFAC) has been applied to analysis of certain oil pollutants, such as identification of mineral oil types, in "research on oil identification method based on three-dimensional fluorescence spectroscopy" (tianjin university, 2012), gasoline, diesel oil and mixed oil are used as original oil samples, and a pure component model of the mineral oil is established by utilizing parallel factor analysis, so that identification of the mineral oil types is carried out, and composition information of the mixture is provided; or applied to the field of food safety, vegetable oil quality detection and the like, such as the edible blend oil detection method based on the parallel factor analysis method and experimental research (Yanshan university, 2013.) in the article, sunflower oil, soybean oil and peanut oil are adopted to simulate edible blend oil, and qualitative and quantitative detection is carried out on the edible blend oil by combining a three-dimensional fluorescence spectrum technology and a parallel factor analysis algorithm, so as to be used as a supplement of the detection technology of the types and the contents of the main components of the edible blend oil.
Therefore, the three-dimensional fluorescence spectrum is mostly applied to mineral oil identification, oil product detection or detection of trace mineral oil in simulated surface water by combining with a parallel factor analysis method (PARAFAC), and is mostly in a laboratory research stage, so that the surface water surface floating oil can be quickly analyzed and traced to the source, and the actual requirement of controlling the source of oil pollutants is rarely met. The main reasons are that the composition of the surface water body changes greatly, the components are complex, other organic matters in the water body can generate fluorescence peaks in a three-dimensional fluorescence spectrum, the process of extracting oil pollutants from the surface water body by using an organic solvent or a solid phase extraction column is complicated and time-consuming, and other soluble organic matters in the water body can be extracted. In addition, the surface oil slick of the surface water is a mixed system, the source and the proportion of different oil pollutants are identified from the mixed system, the interference problem of similar oil is required to be considered, the existing oil pollution identification method is often lack of verification, and the reliability of the identification result is unknown. Therefore, the existing detection method has the defects of complex operation, time consumption, low practicability and easy interference by other substances in water. Therefore, it is necessary to establish a quick and cheap surface water surface floating oil tracing method integrating sampling, analysis and identification and verify the method.
Disclosure of Invention
The invention aims to solve the technical problem of providing a method for quickly tracing surface water floating oil based on three-dimensional fluorescence spectroscopy, which is simple to operate, low in cost, safe, pollution-free, strong in practical applicability and free from interference of other substances in water.
The technical scheme adopted by the invention for solving the technical problems is as follows: a method for quickly tracing surface floating oil on the surface of surface water based on a three-dimensional fluorescence spectroscopy comprises the following steps:
(1) sample pretreatment
A. Surface water surface oil slick extraction: placing the polypropylene composite oil absorption material on the surface of an oil-polluted water body, extracting floating oil on the surface, immersing the oil-polluted water body in an organic solvent, and carrying out ultrasonic treatment for 15min to fully dissolve the oil-polluted oil extracted from the oil absorption material in the organic solvent to obtain a sample to be detected; immersing a clean polypropylene composite oil absorption material in the same organic solvent, and carrying out ultrasonic treatment for 15min to obtain an organic solution as a blank sample;
B. data acquisition and processing: measuring three-dimensional fluorescence spectra of a sample to be measured and a blank sample, deducting the fluorescence data of the blank sample from the fluorescence data of the sample to be measured to remove a Raman scattering effect, setting the fluorescence intensity of Rayleigh scattering rays as missing, and setting triangular area data with the emission wavelength smaller than the excitation wavelength on the fluorescence spectra as zero to obtain the three-dimensional fluorescence spectrum data of the sample to be measured;
(2) identification model building
A. Establishing a correction sample set database: dissolving 95# gasoline, 0# diesel oil, waste engine oil and commercially available salad oil in an organic solvent to prepare a mixed standard sample; fully and uniformly mixing all prepared mixed samples, determining a three-dimensional fluorescence spectrum, and determining the three-dimensional fluorescence spectrum of the organic solvent as a blank sample; subtracting the fluorescence data of the blank sample from the fluorescence data of the mixed sample to remove a Raman scattering effect, setting the fluorescence intensity of Rayleigh scattering rays as missing, and setting triangular area data with the emission wavelength smaller than the excitation wavelength on a fluorescence spectrum as zero to obtain a three-dimensional fluorescence spectrum database of a correction sample set;
B. establishing an analysis model: analyzing the three-dimensional fluorescence spectrum data of the correction sample set by using a parallel factor (PARAFAC) algorithm tool box in Matlab software to obtain fluorescence spectrum characteristic peaks capable of indicating four oils, and establishing a quantitative regression model based on EEM;
(3) identification of type and proportion of oil contaminants
Performing PARAFAC analysis on the three-dimensional fluorescence spectrum data of the sample to be detected and the three-dimensional fluorescence spectrum data of the correction sample set in Matlab software, identifying the type of oil pollutants in the sample to be detected according to the analyzed fluorescence spectrum characteristic peaks, substituting the fluorescence response values of the characteristic peaks into an EEM quantitative regression model, and converting the concentration data of the oil pollutants into the proportion of the oil pollutants, namely obtaining the type and the proportion of the oil pollutants, so as to realize the rapid tracing of the surface water surface floating oil;
(4) and (3) model correction: and (3) if the three-dimensional fluorescence spectrum intensity of the oil pollutants in the actual sample exceeds the upper and lower detection limit values of the three-dimensional fluorescence spectrum of the correction sample set, diluting or concentrating the concentration of the corresponding sample by a plurality of times, and identifying the type and the proportion of the oil pollutants through the step (3).
Further, the three-dimensional fluorescence measurement scanning conditions in the step (1) are as follows: hitachi F-4600 fluorescence photometer, the excitation wavelength is 220-450nm, the scanning interval is 5nm, the emission wavelength is 260-600nm, the scanning interval is 1nm, the slit width is 5nm, and the scanning speed is 2400 nm.min -1 。
Further, in the step (2) A, 95# gasoline, 0# diesel oil, used oil and commercially available salad oil are respectively dissolved in an organic solvent, the preparation concentration ranges are 3-15ppm of gasoline, 2-10ppm of diesel oil, 2-70ppm of used oil and 5000ppm of vegetable oil 100-. The proportion can be determined by the empirical value of the occurrence of the oil in the water body.
Further, the PARAFAC algorithm in step (2) B is based on trilinear decomposition theory, i.e. assuming that at a certain excitation emission wavelength, the fluorescence intensity of a certain component is a trilinear function of the component concentration and specific absorption/emission spectrum properties, the model is as follows:
wherein F refers to the component number in the model and can be determined by a kernel consistency function;
is a sample
At the emission wavelength
Excitation wavelength of
Fluorescence intensity data in time, i.e. cubic arrays of F
Constituent elements of (1);
scoring the factors to reflect the composition
In the sample
Percent concentration in (1), i.e. component matrix
(
) Constituent elements of (1);
for supporting, with a component at the emission wavelength
The fluorescence quantum yield of time is linearly related, i.e. component matrix
(
) Constituent elements of (1);
is a load, with the components
At an excitation wavelength of
The specific absorption coefficient of time is in direct proportion, i.e. component matrix
(
) Constituent elements of (1);
representing residuals including noise and unmodeled data signals. The solution is to reduce the residual Sum of Squares (SSR) by using an alternative least square algorithm when the SSR is used<10 -6 When it is time, the model is considered to have reached convergence.
The invention principle is as follows: the rapid analysis method mainly utilizes the low density and selective adsorption characteristics of the polypropylene composite oil absorption material, and can float on the water surface to adsorb the floating oil on the water surface without adsorbing other interfering substances in the water, thereby realizing the rapid extraction of the floating oil on the surface of the surface water. For example, for petroleum (gasoline, diesel oil, engine oil, etc.), the types and contents of polycyclic aromatic hydrocarbons contained in the oils are different, and the structure of the polycyclic aromatic hydrocarbons determines the characteristics of the fluorescence spectrum, including the shape and peak information of the fluorescence spectrum. In the case of vegetable oils, the dienoic and trienoic acids, tocopherols, etc. in their components are also fluorescent coloring substances. Under the same test environment and steps of different oil substances, the measured fluorescence spectra have great difference, the peak value information and the spectrum shape of the spectra are different, and the PARAFAC algorithm can be adopted to decompose the three-dimensional fluorescence spectrum superposed by a large amount of complex fluorescence information into relatively independent characteristic fluorescence peaks capable of representing several oils, thereby providing feasibility and theoretical basis for the analysis and traceability of oil pollutants based on the three-dimensional fluorescence principle. In addition, the properties of polycyclic aromatic hydrocarbon compounds and organic matters containing unsaturated bonds in the oil substances are more stable than those of saturated hydrocarbon substances and alkyl substances, and the polycyclic aromatic hydrocarbon compounds and the organic matters containing unsaturated bonds can keep stable and unchanged in structure under the external weathering condition, so that the polycyclic aromatic hydrocarbon compounds and the organic matters containing unsaturated bonds can be used as characteristic indexes for analyzing the oil pollutants. The invention utilizes the principle to establish a quantitative regression model of the characteristic fluorescence peak and several oils, thereby achieving the purpose of quickly analyzing and tracing the surface oil slick of the surface water.
Compared with the prior art, the invention has the advantages that: the invention relates to a method for quickly tracing surface water floating oil based on a three-dimensional fluorescence spectrum method, which aims at the practical requirement of controlling the source of surface water oil pollutants, establishes a set of complete surface water floating oil quick tracing flow integrating sampling, analysis and identification, fully utilizes the low density and selective adsorption characteristics of a polypropylene composite oil absorption material and the characteristic fluorescence peak of a three-dimensional fluorescence spectrum to interpret several oils and proportions contained in the surface water floating oil, has the advantages of very simple operation, short detection process time and low cost, can judge and trace the oil pollutants by carrying out PARAFAC analysis after collecting the three-dimensional fluorescence spectrum data of a sample, and only needs 10 minutes in the whole detection process. In addition, the detection method only needs a very small amount of organic solvent, has low cost, basically does not generate the problem of environmental pollution, and does not damage the health of detection personnel. The method is rapid, accurate and strong in practicability for analyzing and evaluating the oil pollutants in the surface floating oil of the surface water, and the validity of the identification result is verified by using a gas chromatography-mass spectrometer GC-MS. The detection method provided by the invention becomes a rapid, efficient and environment-friendly detection method for analyzing and tracing the oil pollutants in the surface oil of the surface water, and can provide theoretical basis and data support for source control of the oil pollutants in the surface water.
In conclusion, the invention provides a method for quickly tracing surface water floating oil by integrating sampling, analysis and identification, and relates to the field of effective extraction of oil pollutants, separation of mixed oil and proportion identification thereof, in particular to a method for quickly tracing the composition and the proportion of the surface water floating oil by using a low-density polypropylene composite oil absorption material to extract the surface water floating oil and a three-dimensional fluorescence spectrometry, such as the automobile industry, the mechanical industry, the catering industry and the like, can provide a theoretical basis for controlling and governing surface water oil pollution, and can also be applied to emergency monitoring of sudden oil leakage.
Drawings
FIG. 1 is a flowchart illustrating the operation steps of the method for quickly tracing the surface oil slick of the surface water according to the present invention;
FIG. 2 is a three-dimensional fluorescence spectrum of a gasoline standard with a concentration of 10 ppm;
FIG. 3 is a three-dimensional fluorescence spectrum of a diesel standard at a concentration of 5 ppm;
FIG. 4 is a three-dimensional fluorescence spectrum of a used oil standard at a concentration of 5 ppm;
FIG. 5 is a three-dimensional fluorescence spectrum of a vegetable oil standard at a concentration of 1000 ppm;
FIG. 6 shows 6 components analyzed by PARAFAC analysis of the mixture of four oils, wherein C1 represents the characteristic peak of vegetable oil, and the possible chromogenic substances are tocopherol, tocotrienol and derivatives thereof; c2 represents the characteristic peak of diesel oil, but is influenced by waste engine oil, and possible chromogenic substances are naphthalene, fluorene and derivatives thereof; c3 represents the characteristic peak of diesel oil, but is influenced by waste engine oil, and possible chromogenic substances are dibenzothiophene and derivatives thereof; c4 represents characteristic peak of used oil, and possible chromogenic substance is benzo [ a ] anthracene, phenanthrene, anthracene and derivatives thereof; c5 represents the characteristic peak of vegetable oil, and possible chromogenic substance is linolenic acid and its derivatives; c6 represents the characteristic peak of gasoline, but is influenced by diesel oil and waste engine oil, and possible chromogenic substance is benzene series;
FIG. 7 is a three-dimensional fluorescence spectrum of a practical sample representative of T2, T3, T4 and T5 in the application example;
FIG. 8 is a graph of correlation analysis of EEM and GC-MS oil identification results, with a solid black line being a linear fit of EEM and GC-MS oil identification results in the calibration sample set, and a gray region being a 95% confidence interval; the blue dispersion point is the identification result of EEM and GC-MS oils of an actual sample, wherein partial negative value points are deleted; a is gasoline, b is diesel oil, c is used oil, d is vegetable oil.
Detailed Description
The invention is described in further detail below with reference to the accompanying examples.
DETAILED DESCRIPTION OF EMBODIMENT (S) OF INVENTION
A method for quickly tracing surface floating oil on the surface of surface water based on three-dimensional fluorescence spectroscopy comprises the following steps as shown in figure 1:
1. sample pretreatment
A. Surface water surface oil slick extraction: placing the polypropylene composite oil absorption material on the surface of water polluted by oil, extracting floating oil on the surface, immersing the material in 200 mL of organic solvent, and carrying out ultrasonic treatment for 15min to fully dissolve the oil pollutants extracted from the oil absorption material in the organic solvent to obtain a sample to be detected; immersing a clean polypropylene composite oil absorption material in the same organic solvent, and carrying out ultrasonic treatment for 15min to obtain an organic solution as a blank sample;
B. data acquisition and processing: measuring the three-dimensional fluorescence spectrums of the sample to be measured and the blank sample, deducting the fluorescence data of the blank sample from the fluorescence data of the sample to be measured to remove a Raman scattering effect, setting the fluorescence intensity of Rayleigh scattering rays as missing, and setting the triangular area data with the emission wavelength smaller than the excitation wavelength on the fluorescence spectrums as zero to obtain the three-dimensional fluorescence spectrum data of the sample to be measured;
2. model building
A. Establishing a correction sample set database: dissolving 95# gasoline, 0# diesel oil, waste engine oil and commercial salad oil in an organic solvent, and preparing a mixed standard sample according to a ratio of 3:5:40:1000, 5:2:70:5000, 5:3:10:2000, 5:5:30:500, 5:6:40:3000, 8:3:50:500, 8:6:30:2000, 10:8:30:5000, 15:2:30:1000 and 15:8:10: 3000. Fully and uniformly mixing all prepared mixed samples, determining a three-dimensional fluorescence spectrum, and determining the three-dimensional fluorescence spectrum of the organic solvent as a blank sample; subtracting the fluorescence data of the blank sample from the fluorescence data of the mixed sample to remove a Raman scattering effect, setting the fluorescence intensity of Rayleigh scattering rays as missing, and setting triangular area data with the emission wavelength smaller than the excitation wavelength on the fluorescence spectrum as zero to obtain three-dimensional fluorescence spectrum data of a corrected sample set; specifically, as shown in fig. 2, 3, 4 and 5, according to the three-dimensional fluorescence spectra of several oil standard products such as gasoline, diesel oil, waste engine oil and commercially available salad oil, the preparation concentration range is 3-15ppm for gasoline and diesel oil, considering the detection limit of the instrument and the intensity of the fluorescence peak of the characteristic peak2-10ppm, 2-70ppm of used engine oil, 100 ppm of vegetable oil and 5000ppm (the unit ppm is volume ratio), 79 parts of mixed solution (mixed standard samples are prepared according to the proportion of 3:5:40:1000, 5:2:70:5000, 5:3:10:2000, 5:5:30:500, 5:6:40:3000, 8:3:50:500, 8:6:30:2000, 10:8:30:5000, 15:2:30:1000 and 15:8:10:3000 respectively, the proportion can be determined by the empirical value of the occurrence content of the oil in the water body), under the specific three-dimensional fluorescence scanning condition: hitachi F-4600 fluorescence photometer, the excitation wavelength is 220-450nm, the scanning interval is 5nm, the emission wavelength is 260-600nm, the scanning interval is 1nm, the slit width is 5nm, and the scanning speed is 2400 nm.min -1 Scanning to obtain a three-dimensional fluorescence spectrum database of a correction sample set;
B. establishing an analysis model: analyzing the three-dimensional fluorescence spectrum data of the correction sample set by using a parallel factor (PARAFAC) algorithm tool box in Matlab software to obtain fluorescence spectrum characteristic peaks capable of indicating four oils, and establishing a quantitative regression model based on EEM; specifically, comparing each component with three-dimensional fluorescence spectrograms of several oil standard products, and determining the oil represented by each component and possible chromogenic substances, wherein as shown in figure 6, C1 represents a characteristic peak of the vegetable oil, and the possible chromogenic substances are tocopherol, tocotrienol and derivatives thereof; c2 represents the characteristic peak of diesel oil, but is influenced by waste engine oil, and possible chromogenic substances are naphthalene, fluorene and derivatives thereof; c3 represents the characteristic peak of diesel oil, but is influenced by waste engine oil, and possible chromogenic substances are dibenzothiophene and derivatives thereof; c4 represents characteristic peak of used oil, and possible chromogenic substance is benzo [ a ] anthracene, phenanthrene, anthracene and derivatives thereof; c5 represents the characteristic peak of vegetable oil, and possible chromogenic substance is linolenic acid and its derivatives; c6 represents the characteristic peak of gasoline, but is influenced by diesel oil and used oil, and the possible chromogenic substance is benzene series. And performing linear regression modeling on the fluorescence intensity values of the components and concentration values of corresponding oils, wherein the obtained response parameters are shown in table 1, and performing binary primary and ternary primary equation fitting modeling on the concentrations of gasoline and diesel oil and a plurality of related components in consideration of the interference condition of characteristic peaks of the gasoline and the diesel oil.
TABLE 1 quantitative regression model based on EEM for several oils
3. Identification of type and proportion of oil contaminants
In Matlab software, PARAFAC analysis is carried out on three-dimensional fluorescence spectrum data of a sample to be detected and three-dimensional fluorescence spectrum data of a correction sample set, the type of oil pollutants in the sample to be detected is identified according to analyzed fluorescence spectrum characteristic peaks, fluorescence response values of the characteristic peaks are substituted into an EEM quantitative regression model, the oil pollutants are converted into the proportion of the oil pollutants according to the concentration data of the oil pollutants, the type and the proportion of the oil pollutants are obtained, and the quick tracing of surface water surface floating oil is realized.
4. And (3) model correction: and (3) if the three-dimensional fluorescence spectrum intensity of the oil pollutants in the actual sample exceeds the upper and lower detection limit values of the three-dimensional fluorescence spectrum of the correction sample set, diluting or concentrating the concentration of the corresponding sample by a plurality of times, and identifying the type and the proportion of the oil pollutants through the step (3).
5. And (3) GC-MS verification: measuring PAHs and fatty acid contents of the corrected sample set by GC-MS, selecting characteristic PAHs and fatty acid which can indicate several oils, establishing a quantitative regression model based on GC-MS, establishing correlation between EEM and a prediction result of the GC-MS model by using the corrected sample set and actual samples, and evaluating the oil identification effect of the EEM model. For example, toluene for gasoline, fluorene for diesel, benzo [ a ] anthracene for used oil, and linolenic acid for vegetable oil, a quantitative regression model based on GC-MS was established as shown in Table 2. And establishing the correlation between the EEM and the prediction result of the GC-MS model by using the corrected sample set and the actual sample, and evaluating the oil identification effect of the EEM model, wherein the specific test process is illustrated by an application embodiment.
TABLE 2 GC-MS based quantitative regression models for several oils
The PARAFAC algorithm is based on the trilinear decomposition theory, that is, assuming that the fluorescence intensity of a certain component is a trilinear function of the concentration of the component and specific absorption/emission spectrum properties at a certain excitation emission wavelength, the model is as follows:
Application examples
The floating of the river surface is obvious for the river which is seriously polluted by oilAnd positioning and sampling the river reach with the oil film, and selecting 13 sampling points in total, wherein the names of the sampling points are recorded as T1-T13. And (3) placing the clean oil absorption material at the position of the oil film on the water surface to enable the clean oil absorption material to fully absorb the floating oil, and wrapping and storing the oil absorption material by using tin foil paper. Immersing the oil absorption material for absorbing the oil film on the water surface in an organic solvent with a certain volume, and carrying out ultrasonic treatment for 15min to obtain a sample to be detected; the clean oil absorbing material was treated in the same way to obtain a blank. Adding the sample into a quartz cuvette, placing the cuvette in a Hitachi F-4600 fluorescence spectrophotometer, setting an excitation wavelength of 220-450nm, a scanning interval of 5nm, an emission wavelength of 260-600nm, a scanning interval of 1nm, a slit width of 5nm and a scanning speed of 2400 nm-min -1 The sample is scanned and fluorescence data for the sample and blank is obtained. The three-dimensional fluorescence spectrum of a part of typical samples is shown in fig. 7, and it can be seen that the three-dimensional fluorescence spectrum of the actual sample is not interfered by soluble organic matters in surface water, and further proves that the sampling method provided by the invention has good anti-interference performance and strong practical applicability. In Matlab, the spectral data of the calibration sample set and the sample are analyzed by using a PARAFAC algorithm tool box, components in the result which meet the characteristic fluorescence spectrum peak position of the oil standard are selected, the corresponding fluorescence intensity data are derived and substituted into an EEM quantitative regression model, the proportion of several oils is calculated, and the composition and the source of oil pollutants are further analyzed, as shown in Table 3.
TABLE 3 analysis of the tracing results of the oil-contaminated river reach
As can be seen from table 3, gasoline and vegetable oil are difficult to be detected in surface water floating oil pollution, because gasoline is light oil, contains a large amount of highly volatile short-chain saturated hydrocarbons and benzene series, and more than 70% of gasoline is almost completely lost through physical evaporation, weathering and other processes; as for vegetable oil, as urban domestic sewage collection systems are improved day by day, the direct drainage of kitchen wastewater is effectively treated, so that the detection rate of vegetable oil in surface water floating oil is not high, but it is worth noting that the detection rate of vegetable oil in floating oil is often higher than that of other oils, which indicates that the leakage and the steal drainage of kitchen wastewater are generally concentrated and continuous. A certain amount of diesel oil and engine oil are detected in almost all actual floating oil samples, which indicates that gas stations, road construction, machinery industry, automobile industry and the like can be potential leakage sources, and in addition, oil stains on the road surface can enter water bodies through surface runoff to cause oil pollution of surface water.
Further, the oil identification effect of the present invention was verified by GC-MS, as shown in fig. 8, the correlation analysis chart of EEM with the GC-MS gasoline and diesel identification results in the calibration sample set has the following characteristics: (1) the slope is close to 1; (2) the intercept is close to 0 (the intercept of the vegetable oil identification result is slightly larger, which is caused by the higher identification concentration range of the vegetable oil); (3) r 2 >0.85，p<0.05. This indicates that the oil identification results of the EEM and GC-MS models have good consistency in the calibration sample set, and the prediction accuracy of petroleum products is slightly higher than that of vegetable oil. For the actual sample, the GC-MS model verifies the characteristic of the gasoline which is difficult to detect in the surface water floating oil again; the identification results of the diesel oil and the engine oil are densely distributed at two sides of a fit line, which shows that in an actual surface water floating oil sample, the EEM model has better predictability on diesel oil and engine oil pollutants; the identification result of the GC-MS model on the vegetable oil also proves that part of the kitchen waste water is still discharged into a river at present, and the EEM model can effectively indicate the potential input of the kitchen waste water.
Therefore, the rapid tracing technology of surface water floating oil, which integrates sampling, analysis and identification, developed by the invention can be effectively applied to actual water bodies, has the advantages of low price, rapidness, time saving, environmental protection and the like, has high accuracy of identification results, practically meets the practical requirements that the source of the composite oil pollution in the surface water is difficult to trace and the composite oil pollution is accurately identified, provides technical support for the control and treatment of the surface water oil pollution or sudden oil leakage, and has wide application prospect.
The above description is not intended to limit the present invention, and the present invention is not limited to the above examples. Those skilled in the art should also realize that changes, modifications, additions and substitutions can be made without departing from the true spirit and scope of the invention.
Claims (4)
1. A method for quickly tracing surface floating oil on the surface of surface water based on a three-dimensional fluorescence spectroscopy is characterized by comprising the following steps:
(1) sample pretreatment
A. Surface water surface oil slick extraction: placing the polypropylene composite oil absorption material on the surface of an oil-polluted water body, extracting floating oil on the surface, immersing the oil-polluted water body in an organic solvent, and carrying out ultrasonic treatment for 15min to fully dissolve the oil-polluted oil extracted from the oil absorption material in the organic solvent to obtain a sample to be detected; immersing a clean polypropylene composite oil absorption material in the same organic solvent, and carrying out ultrasonic treatment for 15min to obtain an organic solution as a blank sample;
B. data acquisition and processing: measuring three-dimensional fluorescence spectra of a sample to be measured and a blank sample, deducting the fluorescence data of the blank sample from the fluorescence data of the sample to be measured to remove a Raman scattering effect, setting the fluorescence intensity of Rayleigh scattering rays as missing, and setting triangular area data with the emission wavelength smaller than the excitation wavelength on the fluorescence spectra as zero to obtain the three-dimensional fluorescence spectrum data of the sample to be measured;
(2) identification model building
A. Establishing a correction sample set database: dissolving 95# gasoline, 0# diesel oil, waste engine oil and commercially available salad oil in an organic solvent to prepare a mixed standard sample, fully and uniformly mixing all prepared mixed samples, measuring a three-dimensional fluorescence spectrum, and measuring the three-dimensional fluorescence spectrum of the organic solvent to serve as a blank sample; subtracting the fluorescence data of the blank sample from the fluorescence data of the mixed sample to remove a Raman scattering effect, setting the fluorescence intensity of Rayleigh scattering rays as missing, and setting triangular area data with the emission wavelength smaller than the excitation wavelength on a fluorescence spectrum as zero to obtain a three-dimensional fluorescence spectrum database of a correction sample set;
B. establishing an analysis model: analyzing the three-dimensional fluorescence spectrum data of the correction sample set by using a parallel factor algorithm tool box in Matlab software to obtain fluorescence spectrum characteristic peaks capable of indicating four oils, and establishing a quantitative regression model based on EEM;
(3) identification of type and proportion of oil contaminants
Performing PARAFAC analysis on the three-dimensional fluorescence spectrum data of the sample to be detected and the three-dimensional fluorescence spectrum data of the correction sample set in Matlab software, identifying the type of oil pollutants in the sample to be detected according to the analyzed fluorescence spectrum characteristic peaks, substituting the fluorescence response values of the characteristic peaks into an EEM quantitative regression model, and converting the concentration data of the oil pollutants into the proportion of the oil pollutants, namely obtaining the type and the proportion of the oil pollutants, so as to realize the rapid tracing of the surface water surface floating oil;
(4) and (3) model correction: and (3) if the three-dimensional fluorescence spectrum intensity of the oil pollutants in the actual sample exceeds the upper and lower detection limit values of the three-dimensional fluorescence spectrum of the correction sample set, diluting or concentrating the concentration of the corresponding sample by a plurality of times, and identifying the type and the proportion of the oil pollutants through the step (3).
2. The method for rapidly tracing surface water floating oil based on three-dimensional fluorescence spectroscopy according to claim 1, wherein: the scanning conditions for three-dimensional fluorescence measurement in the step (1) are as follows: hitachi F-4600 fluorescence photometer, the excitation wavelength is 220-450nm, the scanning interval is 5nm, the emission wavelength is 260-600nm, the scanning interval is 1nm, the slit width is 5nm, and the scanning speed is 2400 nm.min -1 。
3. The method for rapidly tracing surface water floating oil based on three-dimensional fluorescence spectroscopy according to claim 1, wherein: in the step (2), 95# gasoline, 0# diesel oil, used oil and commercially available salad oil are respectively dissolved in an organic solvent, the preparation concentration ranges are 3-15ppm of gasoline, 2-10ppm of diesel oil, 2-70ppm of used oil and 5000ppm of vegetable oil, and a mixed standard sample is prepared according to the proportion of 3:5:40:1000, 5:2:70:5000, 5:3:10:2000, 5:5:30:500, 5:6:40:3000, 8:3:50:500, 8:6:30:2000, 10:8:30:5000, 15:2:30:1000 and 15:8:10:3000 respectively.
4. The method for rapidly tracing surface water floating oil based on three-dimensional fluorescence spectroscopy according to claim 1, wherein: the PARAFAC algorithm in the step (4) is based on the trilinear decomposition theory, that is, assuming that when a certain excitation emission wavelength is adopted, the fluorescence intensity of a certain component is a trilinear function of the component concentration and specific absorption/emission spectrum properties, and the model is as follows:
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