Methods for Identifying Weathered Gasoline Supply Sources

Abstract

A method for identifying weathered gasoline supply sources involves performing gas chromatography-mass spectrometry analysis on weathered gasoline samples, followed by an identification suitability screening step. A combination of multiple identification compounds is then selected, and 40 diagnostic ratios are calculated based on these combinations. Principal component scores are then calculated, and a scatter plot is generated. The method allows for the identification of weathered gasoline supply sources through the calculated principal component scores or the generated scatter plot.

Description

Technical Field

[0001] The present invention relates to gasoline identification and analysis technology, and in particular to a method for identifying the supply source of weathered gasoline. Prior Art

[0002] When oil leakage occurs in the underground oil storage tank system and causes soil and groundwater pollution, it will cause harm to the surrounding environment and public health. Therefore, the pollution problem of gas stations has always been an issue of increasing concern to environmental protection authorities. After the opening of gas stations to private enterprises, the oil market competition is fierce, and the gas station operators or the oil supply sources used are frequently changed. When oil leakage pollution incidents occur, it is often difficult to clarify the responsibility for the pollution problem. Therefore, it is urgent to establish oil pollution investigation and identification technology.

[0003] The invention patent case No. I762067 "Method for Identifying Gasoline Supply Sources" approved by the applicant of this case is proposed to solve the above-mentioned problem. Although the identification method provided by the previous patent case can achieve the effect of distinguishing different gasoline supply sources, it is mainly used for the identification of fresh gasoline. However, after gasoline leaks into the soil or groundwater, it undergoes weathering such as volatilization, dissolution or biodegradation. Many light components that can be used to identify the source of the oil have been dissipated, making the identification method unsuitable for the identification and analysis of weathered gasoline. Therefore, there is still room for improvement.

[0004] In view of this, how to improve the above problems is the primary issue that the present invention aims to solve. Summary of the invention

[0005] The main purpose of the present invention is to provide a method for identifying the supply source of weathered gasoline, which has the effect of distinguishing different supply sources of weathered gasoline.

[0006] To achieve the above-mentioned purpose, the present invention provides a method for identifying a weathered gasoline supply source, comprising the following steps:

[0007] (A) Sample acquisition: Obtain at least one (or more) weathered gasoline samples;

[0008] (B) Gas chromatography-mass spectrometry analysis: All weathered gasoline samples were subjected to gas chromatography-mass spectrometry analysis to obtain their TIC, C 3-Benzenes, C 4-Benzenes, C 5-Benzenes and Indanes spectra respectively;

[0009] (C) Screening of the suitability of the spectrum for identification: The TIC, C 3-Benzenes, C 4-Benzenes and C 5-Benzenes spectra obtained after gas chromatography-mass spectrometry analysis are examined to determine whether the weathered gasoline sample is suitable for traceability identification; if so, proceed to step (D); if not, the sample is considered unidentifiable;

[0010] (D) Selecting identification compounds and calculating their diagnostic ratios: selecting a plurality of identification compounds from the spectra that have passed the identification suitability test, and calculating 40 diagnostic ratios based on the selected identification compounds;

[0011] (E) Calculation of principal component scores: The method of using the diagnostic ratio is determined by whether there is an established database. If there is, the calculated diagnostic ratio is imported into the database for principal component analysis, and the scores of the first and second principal components are calculated to produce a scatter plot; if there is no such database, the score of the first principal component is calculated using the characteristic equation, or the scores of the first and second principal components are calculated using the characteristic equation and a scatter plot is produced;

[0012] (F) Supply source determination: Based on the scatter plot produced in step (E) or the score of the first principal component calculated using the characteristic equation, determine whether the supply source can be clearly identified; if so, output the identification result; if not, it means that the identification cannot be made.

[0013] The above-mentioned objects and advantages of the present invention can be easily understood from the following detailed description of the selected embodiments and the accompanying drawings. Simple diagram description

[0014] Figure 1 is a schematic diagram of the identification process of the present invention. FIG. 2A is a schematic diagram of a TIC reference spectrum obtained by GC / MS analysis in the present invention. FIG. 2B is a schematic diagram of a reference spectrum of C 3-Benzenes obtained by GC / MS analysis in the present invention. FIG. 2C is a schematic diagram of a reference spectrum of C 4-Benzenes obtained by GC / MS analysis in the present invention. FIG. 2D is a schematic diagram of a reference spectrum of C 5-Benzenes obtained by GC / MS analysis in the present invention. FIG. 2E is a schematic diagram of the reference spectrum of Indanes obtained by GC / MS analysis of the present invention. FIG. 3 is a schematic diagram of the process of identifying suitability screening of the present invention. Implementation

[0015] Please refer to FIG. 1, which shows the weathered gasoline supply source identification method provided by the present invention, which includes the following steps:

[0016] (A) Sample acquisition: Obtain multiple weathered gasoline samples; samples can include floating oil, soil or water samples, with floating oil being the first priority, followed by soil samples with higher gasoline concentrations, preferably clayey samples, and finally water samples, preferably fresh water samples. Treatment methods that promote microbial degradation can easily increase the difficulty of sample identification and should be avoided. Diesel blending can also interfere with gasoline identification, so it is better to use samples without diesel or with low diesel concentrations. In general, the principle is to obtain samples that are closest to fresh gasoline.

[0017] (B) Gas chromatography-mass spectrometry analysis: All weathered gasoline samples are subjected to gas chromatography-mass spectrometry analysis (GC / MS or Purge&Trap / GC / MS), and the gas chromatography-mass spectrometry analysis mainly focuses on the heavier part of gasoline, that is, the aromatic hydrocarbon part, to obtain the spectra of TIC, C 3-Benzenes, C 4-Benzenes and C 5-Benzenes respectively (as shown in Figures 2A to 2D); among them, diesel range total petroleum hydrocarbon analysis can also be performed as needed to evaluate whether there is significant diesel interference. If there is significant diesel interference, the sample will be excluded. The chromatographic column for gas chromatography-mass spectrometry analysis can be a low-polarity 100-meter column (such as HP-1) or a 60-meter column dedicated to volatile organic compounds (such as DB-624). The two columns have similar separation effects on the main identification compounds, but the spectra presented by some non-identification compounds will be slightly different. Purge & Trap, Headspace or SPE can all be used as sample pre-analysis processing equipment. The selection can be based on sample concentration or existing equipment conditions. However, special attention should be paid to cross-contamination between samples, especially when there is a possibility of oil products being supplied by Formosa Plastics and CPC at the same time, and repeated confirmation should be performed. In addition, when using Purge & Trap / GC / MS for identification analysis, since Purge & Trap has a sample concentration effect, the concentration should not be too high to avoid cross-contamination. Headspace or SPE can be used with GC / FID to test the sample concentration before taking an appropriate amount of sample for identification analysis. If SPE is used as a sample pre-analysis processing equipment, identification analysis should be performed directly with the eluate, and concentration procedures such as vacuum concentration or nitrogen blowing concentration should not be performed, because this will cause the loss of more volatile identification components and lead to distortion of the diagnostic ratio. When using DB-624 or a column of the same nature for separation, the signal peak between C4B6 and C4B5 can distinguish the difference between CPC and Formosa Plastics products. CPC products have only one signal peak, while Formosa Plastics products have two signal peaks, which form three significantly identifiable signals with C4B6 at approximately equal distances. However, the signal peak in the middle (a dicyclopentadiene derivative) will shift in position due to the separation effect of the column used. However, this feature only applies to oil products produced after 2017, and there is still uncertainty about oil products produced before that. As for current gasoline, the C5B14 (pentamethylbenzene) signal peak of Formosa Plastics products is generally smaller than that of CPC products, which can also assist in the identification of oil products. However, the C5B14 signal strength will increase due to oil weathering. It has also been found that some CPC gasoline signals are very weak. Therefore, the signal strength alone cannot be used as the basis for supply source identification. Similarly, this feature only applies to oil products after 2017, and oil products before that may not have this phenomenon.

[0018] (C) Screening of the suitability of the spectrum for identification: Check the TIC, C 3-Benzenes, C 4-Benzenes and C 5-Benzenes spectra obtained after gas chromatography-mass spectrometry analysis to determine whether the weathered gasoline sample is suitable for traceability identification; if so, proceed to step (D); if not, it is a weathered gasoline sample that cannot be identified and should be discarded. Due to the results of laboratory simulation tests and identification analysis of real samples on site, various weatherings will affect the identification diagnostic ratios, among which microbial degradation is the most difficult to overcome, and it is even impossible to obtain a set of diagnostic ratios that can be widely used through parameter selection. Therefore, it is necessary to select samples that are close to fresh gasoline for identification analysis as much as possible. After the GC / MS analysis is completed, the screening of whether the sample is suitable for identification can be started.

[0019] The following forensic suitability screening procedure is based on the selection of relatively fresh samples. Please refer to Figure 3 for further details. The screening conditions for forensic suitability screening in this step (C) include: (c1) Check the TIC spectrum. If C 2-Benzenes is significant and there is still toluene signal, proceed to the next stage of screening. Otherwise, it is judged as "no"; (c2) Check the C 3-Benzenes spectrum. If 1M3EB>1M4EB, and the spectrum type of the spectrum is similar to that of fresh gasoline, then proceed to the next stage of screening. Otherwise, it is judged as "no". Common differences between the C 3-Benzenes spectrum and the fresh gasoline spectrum are abnormally high IPB and PB signals, or abnormally low 124TMB and abnormally high 123TMB. In this case, it should be judged that the spectra of the two are not similar. (c3) Check the C 4-Benzenes spectrum. If the signal intensity shows C4B3>C4B2, C4B5>C4B4, C4B12>C4B11, then proceed to the next stage of screening. Otherwise, it is determined as "No". In addition, when the signal of C4B3, C4B5 or C4B12 is reduced to half of the signal of the same group, it is recommended to determine it as "No". (c4) Check the C 5-Benzenes spectrum. If the signal intensities of C5B1, C5B2 and C5B3 are not much different, the spectrum passes the identification suitability screening in step (C). Otherwise, it is judged as "no". In addition, when the signal intensities of C5B1, C5B2 and C5B3 are reduced to half of the remaining signal intensities (most commonly, the signals of C5B2 and C5B3 are reduced), it is recommended that it should be judged as "no". If any one of the screening conditions is judged as "No", it means that the sample is not suitable for subsequent traceability analysis and is considered to be unidentifiable.

[0020] (D) Selecting identification compounds and calculating their diagnostic ratios: Select the spectra of Indanes (m / z=117), C 3-Benzenes (m / z=120), C 4-Benzenes (m / z=134) and C 5-Benzenes (m / z=148) extracted in SIM mode with fragment ion monitoring from the spectra that have passed the identification suitability screening, select a combination of multiple identification compounds, and calculate their values for subsequent use according to the 40 diagnostic ratios established by GC / MS analysis and identification. For example, there are 4 identification compounds for Indanes, 8 identification compounds for C 3-Benzenes, 13 identification compounds for C 4-Benzenes, and 14 identification compounds for C 5-Benzenes. It is also possible to selectively perform integral calculations on the compounds required for the diagnostic ratios. As shown in Table 1 below, the combination of diagnostic ratios may include combinations of isomers within the same group, such as: 135TMB / 124TMB, C4B10 / C4B9, C5B3 / C5B5; combinations of different groups, such as: C4B9 / C5B11, 1M2EB / Ind1 or C4B12 / 1M3EB; combinations that highlight the differences of specific compounds, such as: PB / 1M4EB or PB / 123TMB. Then the principal component score coefficients were calculated based on the combination of diagnostic ratios, for example: 135TMB / 124TMB was -0.0302, C4B10 / C4B9 was 0.0238, C5B3 / C5B5 was 0.0153, 1M4EB / 135TMB was -0.0295, 1M4EB / 123TMB was -0.0312, C4B12 / 1M3EB was 0.0287, PB / 1M4EB was -0.0280, and PB / 123TMB was -0.0312. Table 1: Principal component coefficients and descriptive statistics of 40 diagnostic ratios analyzed by GC / MS Variable name Diagnostic ratio name Principal component fraction coefficient average value Standard Deviation Total number of samples analyzed X 1 PB / 1M4EB -0.0281 0.7500 0.1270 237 X 2 135TMB / 1M3EB 0.0317 0.4620 0.1072 237 X 3 135TMB / 124TMB -0.0302 0.2943 0.0403 237 X 4 1M2EB / 124TMB -0.0301 0.2650 0.0944 237 X 5 1M4EB / 135TMB -0.0297 1.0007 0.2688 237 X 6 135TMB / 1M2EB 0.0266 1.1905 0.2473 237 X 7 135TMB / 123TMB -0.0322 1.3242 0.3036 237 X 8 1M3EB / 124TMB -0.0314 0.6994 0.2809 237 X 9 PB / 123TMB -0.0313 1.1117 0.7047 237 X 10 1M4EB / 123TMB -0.0313 1.3930 0.6869 237 X 11 C4B10 / C4B9 0.0236 0.2321 0.0206 237 X 12 C4B11 / C4B12 -0.0231 0.6782 0.0291 237 X 13 C4B13 / C4B12 0.0254 0.3504 0.0364 237 X 14 C4B13 / C4B11 0.0283 0.5185 0.0668 237 X 15 C4B12 / C4B9 0.0277 1.0855 0.0711 237 X 16 C4B12 / 1M2EB 0.0286 0.4937 0.1399 237 X 17 C4B9 / 1M2EB 0.0270 0.4499 0.1082 237 X 18 C5B3 / C5B5 0.0154 0.9759 0.1363 237 X 19 C5B10 / C5B3 0.0273 0.9641 0.1580 237 X 20 C5B12 / C5B3 0.0285 0.7095 0.1730 237 X 21 C5B12 / C5B5 0.0319 0.6929 0.1924 237 X 22 C5B13 / C5B3 0.0286 0.5945 0.1809 237 X 23 C5B13 / C5B5 0.0319 0.5808 0.1916 237 X 24 C5B13 / C5B10 0.0291 0.6033 0.0912 237 X 25 C5B11 / C5B3 0.0247 1.1985 0.3185 237 X 26 C5B11 / C5B5 0.0307 1.1635 0.3167 237 X 27 C5B10 / C5B14 -0.0286 6.6569 6.3703 237 X 28 C5B14 / C5B11 0.0318 0.3044 0.2174 237 X 29 C5B14 / C5B5 0.0319 0.4146 0.3429 237 X 30 C5B14 / C4B12 0.0302 0.0448 0.0273 237 X 31 C4B9 / C5B11 0.0229 5.5730 1.6324 237 X 32 C4B12 / C5B12 0.0269 10.1734 2.9626 237 X 33 Ind1 / Ind2 -0.0278 3.0924 1.3638 237 X 34 Ind4 / Ind1 0.0322 0.5204 0.2047 237 X 35 Ind3 / Ind1 0.0316 0.3676 0.1366 237 X 36 Ind3 / Ind4 -0.0249 0.7149 0.0322 237 X 37 1M2EB / Ind1 0.0316 0.6571 0.4119 237 X 38 124TMB / Ind1 0.0319 3.1731 2.3899 237 X 39 Ind1 / C5B5 -0.0307 30.4555 15.9389 237 X 40 Ind1 / C4B12 -0.0325 6.4698 5.5459 237

[0021] (E) Calculation of principal component scores: The method of using the diagnostic ratio is determined by whether there is an established database; if so, the calculated diagnostic ratio is imported into the database for principal component analysis, and the scores of the first and second principal components are calculated to produce a scatter plot; if not, the score of the first principal component is calculated using the characteristic equation, or the scores of the first and second principal components are calculated using the characteristic equation and then a scatter plot is produced.

[0022] The present invention utilizes the diagnostic ratio of gasoline combined with the principal component analysis method to identify the gasoline of CPC and Formosa Plastics. In the presentation of the results, the scores of the first principal component (PC1) are used to plot the scores of the second principal component (PC2), so that the points of the two oil products on the graph are located on both sides of the X=0 axis. The PC1 scores of the Formosa Plastics gasoline samples obtained by GC / MS analysis of fresh gasoline mainly fall between -1.8 and -0.4, while those of CPC gasoline samples fall between 0.6 and 1.4. That is, the key to truly distinguishing CPC and Formosa Plastics oil products lies in the PC1 score. Therefore, if the PC1 score can be directly calculated, the purpose of identifying the gasoline supply source can be achieved. This approach does not require the use of a complex database, and allows laboratories or units that have identification needs but do not have a database or statistical analysis software to directly obtain the PC1 score by obtaining the established calculation formula, making identification more convenient and easier to promote and apply. In addition, when using GC / MS to identify weathered gasoline, when the PC1 value is between -0.4 and 0.5, more samples must be used to comprehensively evaluate its supply source and, when appropriate, to supplement it with characteristic components for joint analysis. If only one data point is available, the identification result should be retained.

[0023] The PC1 score is the sum of the "component score coefficient (principal component score coefficient)" of each diagnostic ratio calculated using SPSS statistical software and the "standard score" (Standard score, or z-score). The standardized score Z can be expressed as follows: Where, Zi is the standardized score of the i-th diagnostic ratio; Xi is the i-th diagnostic ratio; is the average value of the ith diagnostic ratio; б i is the standard deviation of the ith diagnostic ratio.

[0024] The calculation formula of the PC1 score of the present invention is as follows: PC1_MS40=-0.0281Z 1+ 0.0317Z 2- 0.0302Z 3– 0.0301Z 4– 0.0297Z 5+ 0.0266Z 6- 0.0322Z 7– 0.0314Z 8– 0.0313Z 9– 0.0313Z 10+ 0.0236Z 11- 0.0231Z 12+ 0.0254Z 13+ 0.0283Z 14+ 0.0277Z 15+ 0.0286Z 16+ 0.0270Z 17+ 0.0154Z 18+ 0.0273Z 19+ 0.0285Z 20+ 0.0319Z 21+ 0.0286Z 22+ 0.0319Z 23+ 0.0291Z 24+ 0.0247Z 25+ 0.0307Z 26- 0.0286Z 27+ 0.0318Z 28+ 0.0319Z 29+ 0.0302Z 30+ 0.0229Z 31+ 0.0269Z 32- 0.0278Z 33+ 0.0322Z 34+ 0.0316Z 35- 0.0249Z 36+ 0.0316Z 37+ 0.0319Z 38– 0.0307Z 39- 0.0325Z 40

[0025] (F) Supply source judgment: Based on the scatter plot produced in step (E) or the score of the first principal component calculated using the characteristic equation, judge whether the supply source can be clearly identified; if so, output the identification result; if not, it means that it cannot be identified. If there are only a few one or two samples and their PC1 values are between -0.4 and 0.5, it is recommended to retain the results and carefully evaluate them, and then make an overall judgment after obtaining more samples.

[0026] The following is the applicability evaluation of the weathered gasoline supply source identification method provided by the present invention by obtaining oil samples, soil samples and water samples from the contaminated site and combining them with the laboratory simulation method. Among them, a total of two gas supply centers and six gas stations were obtained. The gas supply centers were mainly for floating oil and water samples, and the gas stations were mainly for soil and water samples. A total of 39 floating oil, 43 soil and 80 groundwater samples were obtained. All samples were identified and analyzed using the method established in the laboratory. After the comprehensive identification sample screening procedure and the results of 40 diagnostic ratio analysis, the gasoline pollution at each site can be reasonably identified. Except for the gasoline supply sources of the two gas stations, including CPC and Formosa Plastics, the rest are all supplied by CPC.

[0027] The floating oil mainly comes from the oil supply center. A total of 4 batches of floating oil samples were obtained from the oil supply center. A total of 39 oil samples were analyzed and identified in the 4 batches. The analysis and identification results of the 39 oil samples show that except for the 3 oil samples in the first batch that were severely weathered or mixed with more diesel, the scatter plots drawn by PC1 and PC2 have obvious deviations, the analysis data of the remaining oil samples are very concentrated, and the results of the 4 batches are not much different. The results of the laboratory volatility simulation and diesel blending test show that the volatility effect and the increase in the amount of diesel blending will cause the data points to shift to the upper right, while the free phase (floating oil) of the dissolution test is almost unaffected by the dissolution effect. Therefore, it can be preliminarily inferred that these three oil samples are mainly affected by the volatility effect and diesel, while the TEX of the remaining floating oils is still very significant, and the light components below toluene still exist. If the spectrum of the laboratory volatility test is compared with the spectrum of the real samples on site, the results of the laboratory and field samples are consistent with each other. Except for the aforementioned severely weathered oil spills, their fingerprints are close to the scenario of evaporation within about 30 hours of the simulation experiment. Within this scenario, the data of the statistical analysis are very concentrated, and PC1 and PC2 have not undergone obvious changes. The analysis results of the real samples on site are completely consistent.

[0028] Soil samples were taken from 6 gas stations, and samples with higher concentrations were mainly selected for identification analysis. A total of 43 soil samples were identified and analyzed. The analytical spectra of the samples were screened for suitability for traceability identification. Reasonable identification results could be obtained by calculating PC1 and PC2 values using 40 diagnostic ratios.

[0029] The denser clay texture makes gasoline less volatile and less soluble in water, which naturally effectively reduces the chance of microbial degradation. Although the leaked gasoline has been in the underground environment for a long time, the correlation ratio of the identification components is still not much different from that of fresh gasoline. In addition, the leakage time is also an important factor. The longer the leakage time in the same environment, the higher the degree of weathering. In the identification process of soil samples, those with higher pollution concentrations have better credibility, but it is not a necessary result. The 43 diagnostic ratios have a good identification effect for fresher gasoline samples, but they are easy to misjudge for the identification of real soil samples in the field, mainly because the C 2-Benzenes correlation ratio is easily affected by weathering. Although C 4-Benzenes and C 5-Benzenes are less volatile, microbial degradation experiments show that C 2-Benzenes, C 3-Benzenes, C 4-Benzenes and C 5-Benzenes are all susceptible to microbial decomposition. Based on the analysis results of laboratory and real samples from contaminated sites, the degradation of alkylbenzene compounds by microorganisms is unpredictable and irregular. Among the field samples, it was found that the C 3-Benzenes components of a few samples would undergo highly selective changes, especially 1-methyl-3-ethylbenzene and 1,2,4-trimethylbenzene. The isopropyl or propyl signals of some samples would also become abnormally strong. The C 4-Benzenes of these specific samples usually also have selective composition changes. It is necessary to check whether the signals of C4B3, C4B5 and C4B12 are weak. If they are less than half of C4B2, C4B4 and C4B11, it is recommended to discard them. The common problem of C 5-Benzenes is that the overall signal of C5B1, C5B2 and C5B3 is reduced, or two selective signals are reduced. For example, when one signal is reduced to half the strength of the other signals, it is recommended that such samples should be discarded. In fact, the samples with fingerprint spectra closer to fresh gasoline should be preferred as the samples for traceability identification.

[0030] In addition, when these key diagnostic ratios with large variations are screened out and 34 diagnostic ratios are used for identification analysis, although the problem of large deviations of data points can be solved, the discrimination of the overall sample is often reduced. Therefore, in order to weigh the credibility of the overall identification, the present invention adopts 40 diagnostic ratios to obtain better results. In the identification of soil samples, it is not appropriate to use a single sample as the basis for identification. Multiple samples at different locations and depths should be taken as much as possible, and the analysis spectrum should be examined in detail to evaluate whether the spectrum has irregular changes due to weathering. If the spectrum has irregular changes, it should be discarded, and the more representative majority of samples should be used as the basis for identification to comprehensively judge the supply source of the leaked oil.

[0031] For groundwater samples, the identification results of wells containing oil spills are relatively good, and the data points also form a good cluster, but the cluster core tends to shift to the upper right compared to the oil spill, which is consistent with the results of the laboratory simulation dissolution test. In addition, since many wells still have oil spills during the first four samplings, that is, there is still a free phase in the underground environment, which can continuously release the dissolved phase into the groundwater, and the gasoline component in the groundwater can maintain a certain degree of freshness. Therefore, although the data points formed by PC1 and PC2 deviate from the free phase in the identification, they are clustered in a reasonable range as a whole, and are consistent with the results of the laboratory dissolution test. Only a few samples have serious deviations. The C 3-Benzenes fingerprint of the groundwater samples shows that the microbial action at this site tends to preferentially degrade 1-methyl-3-ethylbenzene (1M3EB), followed by 1-methyl-4-ethylbenzene (1M4EB), and finally 1-methyl-2-ethylbenzene (1M2EB). The degradation tendency of trimethylbenzenes by microorganisms is preferentially 1,2,4-trimethylbenzene (124TMB), followed by 1,3,5-trimethylbenzene (135TMB), and finally 1,2,3-trimethylbenzene (123TMB). From the chemical structure point of view, ortho-substituted C 3-Benzenes are more difficult to be degraded by microorganisms, which is speculated to be due to steric hindrance. However, not all sites show such a trend. In fact, each trimethylbenzene isomer may be the C 3-Benzene component with the strongest signal after microbial degradation in the water sample.

[0032] Based on the identification results of real samples on site, sampling should be carried out in the highly contaminated areas during sampling planning, and samples from several locations or types should be collected. Floating oil is the first priority for identification samples, but it is advisable to take oil samples that have just entered the well for monitoring floating oil in the well. On-site soil samples with clay texture have a higher probability of successful identification, and clay texture soil should be taken as much as possible for laboratory analysis. When there is gasoline and diesel pollution at the site, the samples are prone to gasoline and diesel mixing. If the identification target is gasoline, samples that are not contaminated by diesel or have a low diesel content should be used for identification. The amount of diesel in the sample needs to be determined separately by the total petroleum hydrocarbon analysis method. The gasoline component in the water sample is easily decomposed by microorganisms, resulting in irregular changes in the diagnostic ratio, so soil samples should be evaluated first for traceability identification. Although clay soil has a better preservation effect, the weathering degree of samples at different depths at the same sampling point may also be different. Therefore, all samples of different types must first go through the identification suitability screening process. Only when the samples are selected as suitable for identification can subsequent statistical analysis be performed. In order to ensure the reliability of the identification results, samples of various types should be obtained for identification as much as possible. If free phase can be obtained, it is better. Even if only one type of sample can be obtained, samples at different points and depths should be obtained as much as possible, and the results of multiple samples should be used to comprehensively judge the source of oil supply. Especially for sites where pollution responsibility needs to be clarified, it should be avoided to use a single sample to determine the responsibility of the entire site.

[0033] The above-mentioned applicability evaluation proves that the weathered gasoline supply source identification method provided by the present invention can indeed be simultaneously applied to the weathered gasoline traceability identification of floating oil, soil or groundwater samples, so as to achieve the effect of distinguishing different supply sources of weathered gasoline, and this method can also be applied to the supply source identification of fresh gasoline.

[0034] However, the disclosure of the above embodiments is only used to illustrate the present invention, not to limit the present invention. Any replacement of equivalent elements should still fall within the scope of the present invention.

[0035] To sum up, those familiar with the art can understand that the present invention can indeed achieve the aforementioned purpose and is in compliance with the provisions of the Patent Law, and therefore an application is filed in accordance with the law.

[0036] (none)

Claims

1. A method for identifying the source of weathered gasoline supply, comprising the following steps: (A) Sample acquisition: obtaining a plurality of weathered gasoline samples; (B) Gas chromatography-mass spectrometry analysis: performing gas chromatography-mass spectrometry analysis on all weathered gasoline samples to obtain their TIC, C3-Benzenes, C4-Benzenes, C5-Benzenes and Indanes spectra respectively; (C) Screening of spectra for identification suitability: examining the TIC, C3-Benzenes, C4-Benzenes and C5-Benzenes spectra obtained after gas chromatography-mass spectrometry analysis respectively to determine whether the weathered gasoline sample is suitable for traceability identification; if so, proceed to step (D); if not, the weathered gasoline sample is unidentifiable; (D) Selecting identification compounds and calculating their diagnostic ratios: selecting a combination of multiple identification compounds from the spectra that have passed the identification suitability, and calculating 40 diagnostic ratios based on the selected identification compounds; (E) Calculation of principal component scores: The method of using the diagnostic ratio is determined based on whether there is an established database. If so, the calculated diagnostic ratio is imported into the database for principal component analysis, and the scores of the first principal component and the second principal component are calculated to make a scatter plot; if not, the score of the first principal component is calculated using the characteristic equation, or the scores of the first principal component and the second principal component are calculated using the characteristic equation and a scatter plot is made; (F) Determination of the supply source: Based on the scatter plot made in step (E) or the score of the first principal component calculated using the characteristic equation, determine whether the supply source can be clearly identified; if so, output the identification result; if not, it means that the identification cannot be made; Among them, The screening conditions of step (C) include: (c1) Checking the TIC spectrum, if C2-Benzenes is significant and there is still a toluene signal, then the next stage of screening is performed, otherwise it is determined as "no"; (c2) Checking the C3-Benzenes spectrum, if 1M3EB>1M4EB, and the spectrum of its spectrum is similar to the spectrum of fresh gasoline, then the next stage of screening is performed, otherwise it is determined as "no"; (c3) Checking the C4-Benzenes spectrum, if its signal intensity shows C4B3>C4B2, C4B5>C4B4, C4B12>C4B11, then the next stage of screening is performed, otherwise it is determined as "no"; (c4) Check the C5-Benzenes spectrum. If the signal intensities of C5B1, C5B2 and C5B3 are not much different, the spectrum passes the identification suitability screening in step (C). Otherwise, it is judged as "no". If any one of the screening conditions is judged as "no", it means that the sample is not suitable for subsequent traceability identification analysis.

2. The method for identifying the source of weathered gasoline supply as described in claim 1, wherein: Weathered gasoline samples include samples of oil spills, soil or water samples.

3. The method for identifying the source of weathered gasoline supply as described in claim 1, wherein: In the gas chromatography-mass spectrometry analysis of step (B), a diesel range total petroleum hydrocarbon analysis is further performed to evaluate whether there is significant diesel interference. If there is significant diesel interference, the sample is excluded.

4. The method for identifying the source of weathered gasoline supply as described in claim 1, wherein: The chromatography column used for gas chromatography-mass spectrometry analysis in step (B) can be a 100-meter column with low polarity or a 60-meter column specially used for volatile organic compounds.

5. The method for identifying the source of weathered gasoline supply as described in claim 1, wherein: In the step (c2) of examining the C3-Benzenes spectrum, when the IPB and PB signals are abnormally high, or the 124TMB is abnormally low and the 123TMB is abnormally high, it should be determined that the C3-Benzenes spectrum is not similar to the spectrum of the fresh gasoline spectrum.

6. The method for identifying the source of weathered gasoline supply as described in claim 1, wherein: In the step (c3) of examining the spectrum of C4-Benzenes, when the signal of C4B3, C4B5 or C4B12 is reduced to half of the signal of the same group, it should be judged as "no".

7. The method for identifying the source of weathered gasoline supply as described in claim 1, wherein: In the step (c4) of examining the spectrum of C5-Benzenes, when the signal intensities of C5B1, C5B2 and C5B3 are reduced to half of the remaining signal intensities, it should be judged as "no".

8. The method for identifying the source of weathered gasoline supply as described in claim 1, wherein: In step (D), the combination of the plurality of diagnostic ratios includes a combination of isomers within the same group, a combination of different groups, or a combination that highlights the differences of a specific compound.

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