A method for on-site classification of unknown organic waste liquids

Abstract

The application discloses a kind of on-site classification methods of unknown organic waste liquid, first using portable gas chromatography-mass spectrometer obtains the full scan data of sample to be classified using full scan mode, according to NIST spectrum library search to determine the organic component in sample, then through similarity calculation and comparison process based on vector space model, sample is classified completely.The on-site classification method of unknown organic waste liquid proposed in the application can quickly and accurately classify unknown organic waste liquid containing complex components.Technical personnel can perform hazard characteristic identification and other work according to the classification results in accordance with relevant technical specifications, overcoming the defects of inaccurate classification or low classification efficiency in the prior art, improving the accuracy of identification results, and providing a scientific basis for subsequent waste liquid management and disposal methods.

Description

Technical Field

[0001] This invention belongs to the field of hazardous waste identification, specifically relating to an on-site classification method for unidentified organic waste liquid. Background Technology

[0002] With the rapid development of the social economy, industrial enterprises are generating more and more types and quantities of waste liquids. In environmental emergency events such as these, it is necessary to identify the hazardous characteristics of the unidentified waste liquids to determine whether they belong to hazardous wastes, and select the appropriate disposal method based on the identification results.

[0003] Currently, the only methods for on-site classification of unidentified waste liquids that cannot be traced are color, odor, acidity / alkalinity tests, and the separation of the waste liquid with water. However, when the unidentified waste liquids to be identified have the same basic properties, the composition of the samples after sampling and testing often differs greatly or even completely. This leads to inaccurate classification and incorrect identification results, affecting the subsequent management and disposal of different types of waste liquids.

[0004] In the classification and hazardous characteristic identification of unidentified organic waste liquids, many waste liquids have complex compositions and unknown types; however, these situations are not unrelated. For a large number of samples, processing the test results by comparing them one by one is computationally intensive, and the comparison results often show significant deviations. While similarity-based dynamic clustering based on vector space models not only reflects the similarity relationships between vectors but also includes the changes in the elements within the vectors, it still has limitations in different application scenarios. This invention discloses a similarity calculation and classification method based on a vector space model, which can quickly and accurately classify unidentified organic waste liquids containing complex components, solving the problems of inaccurate or low-efficiency classification of organic waste liquids in different scenarios. Summary of the Invention

[0005] In view of the shortcomings of the existing technology, the purpose of this invention is to provide an on-site classification method for unidentified organic waste liquid, which can improve the accuracy and efficiency of the classification process.

[0006] To achieve the above objectives, the present invention provides the following technical solution: a method for on-site classification of unidentified organic waste liquid, comprising the following steps: 1) Gas chromatography-mass spectrometry analysis: The VOC and SVOC of the organic waste liquid to be tested on site were qualitatively analyzed using a portable gas chromatograph-mass spectrometer. VOC mass spectrometry conditions were as follows: scan range: 27–300 m / z; scan mode: scan; ion source temperature: 230 °C; quadrupole temperature: 150 °C; interface temperature: 280 °C. SVOC mass spectrometry conditions are as follows: scan range: 35–400 m / z; scan mode: scan; ion source temperature: 320℃; quadrupole temperature: 150℃; interface temperature: 310℃. Based on the retention time, the organic components in the sample were qualitatively identified by searching the NIST spectral library.

[0007] 2) Using the first sample as the reference sample and the other samples as comparison samples, replace the reference sample with a vector. (a1,a2,a3…,a) n ), where a1, a2, a3…, a n To compare the integrated peak areas of each organic component in the reference sample, the sample is converted into a vector. (b1,b2,b3…,b) n ), where b1, b2, b3…, b n To compare the integrated peak areas corresponding to each organic component in the samples, the similarity between the reference sample and the comparison sample is calculated according to the following formula:

[0008] In the formula: Q A→B To measure the similarity between the reference sample and the comparison sample, a i b is the peak area of ​​the i-th common organic compound in the reference sample; i To compare the peak area of ​​the i-th common organic compound in the samples; a k As a reference sample, b k To compare the peak areas of organic matter in the samples, m represents the total number of organic compounds in both the reference and comparison samples.

[0009] Set a similarity threshold for similar substances, and compare the above similarity calculation results with the threshold; 1) If a comparison sample exceeds the threshold, classify the sample and the reference sample into the same category of substances. Then, take one of the samples that does not exceed the preset threshold as the reference sample, examine its similarity with the remaining samples, and classify them accordingly. 2) If the similarity calculation results are all less than the threshold, the reference sample is classified into a separate category of substances. Then, the next sample is used as the reference sample, and the remaining samples are used as comparison samples. The samples are classified according to the above method. This process is repeated until all samples are classified.

[0010] In the practical classification of unidentified waste liquids at the site, the gas chromatography-mass spectrometry results of the samples can serve as a comparison system. All chromatographic peaks detected in the reference and comparison samples form a comparison unit, and the comparison value corresponding to each comparison unit is the ratio of the peak areas. Assume the vector formed by the comparison points of the reference and comparison samples... (a1,a2,a3…,a) n) and vector (b1,b2,b3…,b) n Then, the similarity between the two samples is: In the formula a i b is the peak area of ​​the i-th common organic compound in the reference sample; i The peak area of ​​the i-th common organic compound in the comparison sample is given, where m is the number of common organic compounds in the reference and comparison samples, and a is the peak area of ​​the i-th common organic compound in the comparison sample. i / b i If it is the degree of similarity between the comparison units, then... Let be the average deviation of the m common peaks.

[0011] For samples with a high proportion of organic matter and relatively small differences in peak area, the standard deviation used in this invention better reflects the impact of larger deviations in the numerical values ​​on the evaluation. Therefore, this invention improves the formula, namely... , When all corresponding peak areas show large differences (i.e., (1-a) i / b i ) 2 >1 or a i >2b i )hour, The presence of negative values ​​indicates that the substances belong to different categories. If part of the vector is a comparison unit... i >2b i The greater the relative difference between the contrasting units, the better. The greater the impact, the more significant the effect. When the relative difference of a certain peak exceeds ten or dozens of times, that is... If the value is in the teens or tens, then the peak is... The similarity calculation result plays a dominant role; a negative similarity value indicates that the substances are classified as different categories. Therefore, the improved... It is suitable not only for evaluating the similarity of two samples whose corresponding peak areas are not significantly different, but also for evaluating the similarity of two samples whose corresponding peak areas are significantly different.

[0012] In addition, for the evaluation The area of ​​the common peak is relatively large, but the presence of many non-common peaks in the reference and comparison samples leads to significant bias in the evaluation. This invention incorporates a comparison process between the area of ​​the common peak and the area of ​​all peaks into the formula. To achieve higher accuracy, the proportion of the common peak among all peaks is included in the evaluation.

[0013] Improved That is The product of S and S is the similarity calculation process based on the vector space model of this invention:

[0014] This calculation process can highlight the significant differences in the sample, intuitively distinguish samples that deviate significantly from the reference sample, and quickly separate different categories. It can also sensitively reflect the total impact of the deviation of certain comparative units in the comparative sample from the reference sample on the evaluation, and comprehensively consider the impact of the proportion of non-common peaks in the sample on the evaluation.

[0015] Compared with the prior art, the beneficial effects of the present invention are as follows: The present invention proposes an on-site classification method for unidentified organic waste liquid, which can quickly and accurately classify unidentified organic waste liquid containing complex components. Based on the classification results, technicians can perform hazardous characteristic identification and other work in accordance with relevant technical specifications. This method overcomes the defects of inaccurate classification or low classification efficiency in the prior art, improves the accuracy of identification results, and provides a scientific basis for subsequent waste liquid management and disposal. Attached Figure Description

[0016] Figure 1 This is a flowchart illustrating the specific implementation steps of the similarity threshold-based judgment and classification disclosed in this invention. Detailed Implementation The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of them. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are within the scope of protection of the present invention.

[0017] like Figure 1 As shown, the present invention provides a technical solution: a method for on-site classification of unidentified organic waste liquid, which uses a portable gas chromatograph-mass spectrometer to qualitatively analyze the VOC and SVOC of the organic waste liquid to be tested on-site; VOC mass spectrometry conditions: Scan range: 27~300m / z, Scan mode: scan, Ion source temperature: 230℃, Quadrupole temperature: 150℃, Interface temperature: 280℃; SVOC mass spectrometry conditions: Scan range: 35~400m / z, Scan mode: scan, Ion source temperature: 320℃, Quadrupole temperature: 150℃, Interface temperature: 310℃.

[0018] Based on the retention time, the organic components in the sample were qualitatively identified by searching the NIST spectral library.

[0019] For example: At the scene of an environmental emergency, there are 9 barrels of unidentified organic waste liquid that need to be classified and disposed of. They are numbered A through I. Qualitative analysis is performed under the VOC and SVOC mass spectrometry conditions described in step 1), and the organic components in the samples are qualitatively identified based on retention time and by searching the NIST spectral library. Details are as follows:

[0020] Note: " / " indicates that the substance is not present.

[0021] (2) Using the first sample A as the reference sample and the other samples as the comparison samples, the reference sample is replaced with a vector. (a1,a2,a3…,a) 16 ), where a1, a2, a3…, a 16 To compare the integrated peak areas of each organic component in the reference sample, the sample is converted into a vector. (b1,b2,b3…,b) 16 ), where b1, b2, b3…, b 16 To compare the integrated peak areas corresponding to each organic component in the samples, the similarity between the reference sample and the comparison sample is calculated according to the following formula:

[0022] In the formula: Q A→B To measure the similarity between the reference sample and the comparison sample, a i b is the peak area of ​​the i-th common organic compound in the reference sample; i To compare the peak area of ​​the i-th common organic compound in the samples; a k As a reference sample, b k To compare the peak areas of organic matter in the samples, m represents the total number of organic compounds in both the reference and comparison samples.

[0023] (3) Setting the similarity threshold for similar substances to 0.8, Q is calculated to be... A→B The value is 0.841, therefore it is determined that reference sample A and comparison sample B are classified into the same substance W1.

[0024] Similarly, Q is calculated. A→C The value is -0.609, Q A→D The value is 0.846, Q A→E The value is 0.406, Q A→F The value is 0.868, Q A→G The value is 0.713, Q A→H The value is 0.699, Q A→I The value is 0.862. Therefore, the results of the first round of comparison are: A, B, D, F, and I are classified into one class of substances W1.

[0025] Using C as the reference sample and samples E, G, and H as comparison samples, a second round of comparison was conducted. The calculated Q... C→E The value is 0.908, Q C→G The value is -0.508, Q C→H The value is -0.327. Therefore, the result of the second round of comparison is: C and E are classified into the same substance W2.

[0026] Using G as the reference sample and H as the comparison sample, a third round of comparison was conducted. The calculated Q... G→H The value is 0.905. Therefore, the result of the third round of comparison is: G and H are classified into the same substance W3.

[0027] After three rounds of comparison, the nine samples were classified into three categories: W1, W2, and W3.

[0028] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. It will be apparent to those skilled in the art that the invention is not limited to the details of the exemplary embodiments described above, and that the invention can be implemented in other specific forms without departing from its spirit or essential characteristics. Therefore, the embodiments should be considered illustrative and non-limiting in all respects, and the scope of the invention is defined by the appended claims rather than the foregoing description. Thus, all variations falling within the meaning and scope of equivalents of the claims are intended to be included within the scope of the invention. No reference numerals in the claims should be construed as limiting the scope of the claims.

Claims

1. A method for on-site classification of unidentified organic waste liquid, characterized in that, Includes the following steps: 1) Gas chromatography-mass spectrometry analysis: The VOC and SVOC of the organic waste liquid to be tested on site were qualitatively analyzed using a portable gas chromatography-mass spectrometry analyzer. VOC mass spectrometry conditions are as follows: scan range: 27–300 m / z; scan mode: scan; ion source temperature: 230℃; quadrupole temperature: 150℃; interface temperature: 280℃. SVOC mass spectrometry conditions were as follows: scan range: 35–400 m / z; scan mode: scan; ion source temperature: 320℃; quadrupole temperature: 150℃; interface temperature: 310℃. Based on the retention time, the organic components in the sample were qualitatively identified by searching the NIST spectral library. 2) Using the first sample as the reference sample and the other samples as comparison samples, convert the reference sample into a vector. For (a1, a2, a3…, a n ), where a1, a2, a3…, a n The integral peak area corresponding to each organic component in the reference sample is used; the comparison sample is converted into a vector. For (b1,b2,b3…,b) n ), where b1, b2, b3…, b n To compare the integrated peak areas corresponding to each organic component in the sample; The similarity between the reference sample and the comparison sample is calculated using the following multiplicative two-factor formula: In the formula: Q A→B To measure the similarity between the reference sample and the comparison sample, a i b is the peak area of ​​the i-th common organic compound in the reference sample; i To compare the peak area of ​​the i-th common organic compound in the samples; a k As a reference sample, b k To compare the peak areas of organic matter in the samples, m is the number of organic compounds shared by the reference and comparison samples; 3) Set a similarity threshold for similar substances, and compare the above similarity calculation results with the threshold; 31) If a comparison sample exceeds the threshold, classify the sample and the reference sample into the same category of substances. Then, take one of the samples that does not exceed the preset threshold as the reference sample, examine its similarity to the remaining samples, and classify them. 32) If the similarity calculation results are all less than the threshold, the reference sample is classified into a separate category of substances. Then the next sample is used as the reference sample, and the remaining samples are used as comparison samples. The classification is carried out in the same way until all samples are classified.

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