CN106092981A - Fluorescence method rapid qualitative differentiates fuel oil and the method for crude oil of marine oil overflow - Google Patents

Abstract

The present invention relates to a kind of fuel oil and method of crude oil differentiating marine oil overflow based on oil product fluorescent characteristic rapid qualitative, it is specifically related to a kind of fuel oil utilizing binary nonlinear regression equation quickly to distinguish marine oil overflow based on oil product fluorescent characteristic and crude oil identification method, belongs to marine environmental pollution monitoring and improvement field.The present invention utilizes fuel oil and the method for crude oil of a kind of quick discriminating marine oil overflow of Binary logistic Nonlinear Regression Model Generating, three fluorescent characteristics wavelength are gone out by optimum experimental, and detect the fluorescence intensity parameter as modeling of oil sample using this, thus obtain fuel oil and the quantitative formula of crude oil differentiating marine oil overflow, carry out Logistic regression diagnostics by actual sample.The result that the method quantifies, for differentiating that oil types accuracy is higher, overcomes the defect of current qualitative identification oil kind, and in real time, quickly differentiates that the portable instrument that oil is planted provides a foundation for research and development.

Description

Fluorescence method rapid qualitative differentiates fuel oil and the method for crude oil of marine oil overflow

Technical field

The present invention relates to a kind of fuel oil and side of crude oil differentiating marine oil overflow based on oil product fluorescent characteristic rapid qualitative Method, is specifically related to a kind of fuel oil utilizing binary nonlinear regression equation quickly to distinguish marine oil overflow based on oil product fluorescent characteristic And crude oil identification method, belong to marine environmental pollution monitoring and improvement field.

Background technology

Along with the progress of society, the development of science and technology, the world is increasing to the demand of oil, and this is greatly accelerated oil The expansion of exploitation scale and the development of offshore oil fortune industry.Along with the increase rapidly of offshore oil freight volume, marine oil overflow accident is the most frequent Occur, cause serious oil pollution.Petroleum pollution is primarily referred to as the various hydrocarbon such as alkane, cycloalkane and aromatic hydrocarbons Thing.The marine eco-environment is caused serious harm after entering ocean by oil, the most also gives mariculture industry, fishery, tourist industry Bring huge economic loss etc. marine industries, also the health of the mankind is impacted^[1].Generally, the ocean that oil spill accident causes Pollution will not quickly disappear, and the harm to marine environment will continue the longer time.Therefore, ask to solve marine oil overflow Topic, oils authentication technique needs the most quick and easy；This, for reviewing oil spilling source, finds out accident occurrence cause, investigates and start Thing person's legal responsibility are significant.

At present, finding marine oil overflow source domain, domestic and international marine environment scientific research scholar is carrying out unremitting research always.Deng^[2,3]Once the samples such as 34 kinds of crude oil, and kerosene, gasoline, lubricating oil were determined by GC-FID method The Hydrocarbon fingerprint of product, is used as oil with this and plants mirror method for distinguishing.Wang etc.^[4]GC-FID with GC-MS is combined, right More than 100 kind of saturated hydrocarbons in the sample such as crude oil, oil spilling, more than 50 kind of alkylbenzene based compound, more than 60 kind of polycyclic aromatic hydrocarbon and kind more than 50 Biological Mark Compounds has carried out identification and quantitative analysis.Also has Betti etc.^[5]Research shows radioelement and isotope pair Trace originated the most largely effective.Although domestic spilled oil identification is started late, but recent year scholar also studies The multiple qualitative method differentiating that oil is planted, Gong Jingxia are gone out^[6]GC fingerprint of n-Alkane has been inquired into by an application example Differentiate feasibility and the effectiveness in offshore spilled oil source.Ye Liqun etc.^[7]Utilize GC-FID that oil sample is carried out Preliminary Identification, recycling Fourier infrared spectrograph studies its chemical constitution；Liu Xiao magnitude^[8-10]Propose to utilize n-alkane, fluorescent characteristic, Ni/V, carbon Stable isotope compares δ¹³The multidimensional chemical fingerprint such as C and method differentiate marine weathering crude and bunker fuel oil.Eighties of last century 80 years Proceed by the Study on Identification of marine oil overflow for initial stage China, numerous studies show, fluorescent spectrometry on spilled oil identification Because having the easy advantage such as quickly of mensuration, and it is widely adopted^[11].At present, authentication technique method differs, but these technology are all It is to be analyzed from qualitative angle, it is intended to set up " oil fingerprint " storehouse, do not carry out oil spill type discriminating from quantitative angle.

List of references:

[1] Yu Shude. oil pollution.

http://www.chinabaike.com/article/316/327/2007/2007022051555.htmL.

[2]Fernandez-Varela R,Andrade J M,Muniategui S et al.Identification of fuel samples from the Prestige wreckageby pattern recognition methods.Marine Pollution Bulletin.2008:335–347.

[3]Fernandez-Varela R,Andrade J M,Muniategui S et al.The Comparison of Two Heavy Fuel Oils in Composition and Weathering Pattern,Based on IR,GC- FID and GC-MS Analyses:Application to Prestige Wrea-ckage.Water Research.2009:16-19.

[4]Wang Z D,Fingas M.Oil spill identification.Journal of Chromatography.1999,1:23-26.

[5]Betti M,Boisson F,Eriksson M.et al.Isotop analysis for marine environment studies.Internation Journal of Mass Sepectrometry,2011:1-8.

[6] Gong Jingxia. GC fingerprint of n-Alkane differentiates offshore spilled oil source. Fujian environment, 2002,6:53-54.

[7] Ye Liqun, Zhong Yanqing. utilize gas chromatogram FTIR spectrum method to combine discriminating oil spill source. hand over Logical environmental protection .2002,21 (3): 25-27.

[8] Liu Xiaoxing, Sun Huiqing, Wang Yahui, Fu Chong. distribution of normal alkanes characteristic differentiation sea mixed crude [J]. ring Border chemistry, 2016,35 (2): 305-310.

[9] Liu Xiaoxing, Wang Yi, Qu Ling etc. the research of marine oil overflow chemical fingerprint characteristic. marine environment .2012,31 (6):855-859.

[10] Liu Xiaoxing, Wang Yi, Wang Yanli, the public dimension people. carbon stable isotope is than the mass spectrography discriminating to middle-eastern crude [J.] analytical chemistry, 2012,40 (7): 1104-1108.

[11] Shang Longsheng. synchronous fluorimetry differentiates offshore spilled oil, traffic environment-friendly (water transport version) .1988 (2) 5-10.

[12] He Xiaoqun, Liu Wenqing, applied regression analysis [M]. Beijing: publishing house of the Renmin University of China, 2009:242- 266.

[13] Xia Kunzhuan, Xu Wei, Pan Honglian, Lin Jianwei. deeply resolve the process of SAS: data, analysis optimization is applied with business [M]. Beijing: China Machine Press, 2015:470-500.

Summary of the invention

The present invention utilizes the fuel oil of a kind of quick discriminating marine oil overflow of Binary logistic Nonlinear Regression Model Generating and former The method of oil, goes out three fluorescent characteristics wavelength by optimum experimental, and detects the fluorescence intensity ginseng as modeling of oil sample using this Number, thus obtain discriminating fuel oil and the quantitative formula of crude oil, carry out Logistic regression diagnostics by actual sample.The method The result quantified, for differentiating that oil types accuracy is higher, overcomes the defect of current qualitative identification oil kind, and real for research and development Time, quickly differentiate that the portable instrument that oil is planted provides a foundation.

Fluorescence method rapid qualitative differentiates fuel oil and the method for crude oil of marine oil overflow, comprises the steps:

1. testing sample fluorescence intensity level under 280 ± 2nm, 300 ± 2nm, 332 ± 2nm characteristic wavelength is obtained；

2. the fluorescence intensity level under three characteristic wavelengths step 1. obtained is brought in following formula,

$\mathrm{\π}=\frac{e^y}{1+e^y}$

Wherein, y=-24.39+0.46I_280nm-0.50I_300nm+0.12I_332nm,

Wherein, I_280nmIt is characterized the fluorescence intensity under wavelength 280 ± 2nm；I_300nmBe characterized under wavelength 300 ± 2nm is glimmering Light intensity；I_332nmIt is characterized the fluorescence intensity under wavelength 332 ± 2nm；

When π ∈ [0,0.5), institute's test sample product are crude oil；When π ∈ (0.5,1], institute's test sample product are fuel oil.

The present invention so-called " fluorescence intensity under 280 ± 2nm " refers to characteristic fluorescence corresponding between 278～282nm Intensity, the fluctuation range of the characteristic fluorescence wavelength that instrument allows is ± 2nm.Other characteristic wavelengths adapt to this rule.

Preferred steps of the present invention 1. in, the fluorescence intensity level of described sample utilizes permanent wavelength method to measure.

Preferred steps of the present invention 1. in, the fluorescence intensity level of described sample is to be recorded by molecular fluorescence spectrophotometer.

Step of the present invention 2. described in discrimination formula utilize Logistic regression model to obtain.Logistic regression model belongs to In probabilistic type nonlinear regression model (NLRM), it it is the analysis method utilizing qualitative dependent variable to carry out two classification quantitative statistics.Due to Normality, homogeneity of variance and the argument types of data are not done requirement by Logistic regression model, and have coefficient The advantages such as interpretability^[12], the fluorescent characteristic of oil product measures quick and easy simultaneously, therefore, oil product fluorescent characteristic is applied to In Logistic regression model, in conjunction with Statistical Analysis System (SAS) application software^[13]To oil spill type Carry out quantitative analysis.This will be greatly improved efficiency and accuracy that oil spill type differentiates.

The invention has the beneficial effects as follows: the oil of the present invention is planted and differentiated that model can differentiate marine oil overflow quickly, quantitatively Fuel oil and crude oil, provide a theoretical basis for realizing the research and development of the portable instrument differentiating oil kind online, real-time from now on.

Detailed description of the invention

Following non-limiting example can make those of ordinary skill in the art that the present invention be more fully understood, but not with Any mode limits the present invention.

Test method described in following embodiment, if no special instructions, is conventional method；Described reagent and material, as Without specified otherwise, the most commercially obtain.

Discrimination formula of the present inventionFluorescent characteristics according to oil product is set up, specific as follows:

1, fluorescent characteristics wavelength is chosen

Based in crude oil containing abundant polycyclic aromatic hydrocarbon, fluorescent characteristic is obvious, the present invention have chosen representative, can Come using the oils fluorescent characteristic quickly recorded as characteristic parameter, selection 280 ± 2nm, 300 ± 2nm, 332 ± 2nm characteristic wavelength Measure fluorescence intensity.

2, the mensuration of fluorescence intensity

Utilize molecular fluorescence spectrometry, use permanent wavelength method to measure the fluorescence intensity of above three characteristic wavelength.

3, the foundation of discrimination formula

Using 22 kinds of crude oil and 12 kinds of fuel oil oil samples as analyzing object, measure all analysis objects 280 ± 2nm, 300 Fluorescence intensity under ± 2nm, 332 ± 2nm these three characteristic wavelength.It is used as modeling base with the fluorescence intensity of above-mentioned 34 kinds of oil samples Plinth data, carry out the regression analysis of binary Logistic by the data obtained, according to C statistic, likelihood ratio chi-square statistics amount, HL statistics Amount is as discrimination formula evaluation index.Wherein: C statistic is effective more than 0.9 differentiation；Likelihood ratio chi-square statistics amount trend is the biggest The best, P value is less than 0.05 and the smaller the better；HL statistic trend is the smaller the better, P value is more than 0.05 and is the bigger the better.

The following enforcement example being a binary Logistic regression analysis and calculating:

Using 22 kinds of crude oil and 12 kinds of fuel oil oil samples as analyzing object, under above-mentioned 3 characteristic wavelengths, measure its fluorescence Intensity.Its fluorescence intensity being input in SAS 9.1, be grouped according to the classification of known oil sample, the group of fuel oil is set to 0, the group of crude oil is set to 1.Coding in SAS 9.1^[13], perform the regression analysis of binary Logistic.By to output Interpretation of result, sets up binary Logistic regression model, as follows:

Wherein,

Y=-24.39+0.46I_280nm-0.50I_300nm+0.12I_332nm

If π ∈ [0,0.5), institute's test sample product are crude oil；π ∈ (0.5,1], institute's test sample product are fuel oil.

Model evaluation result: C statistic=0.97 > 0.90 differentiate effective；Degree of freedom is 3 to look into chi-square statistics table, likelihood Than chi-square statistics amount=21.52>7.82, P value=0.001<0.05；Degree of freedom is 8 to look into chi-square statistics table, HL statistic=2.43 <15.51, P value=0.97>0.05.The accuracy rate that crude oil differentiates is more than 90.9%, and the accuracy rate that fuel oil differentiates is 91.7% Above.

Logistic regression routine is write as follows in SAS 9.1

Data dataset name；

InputI_280nm I_300nm I_332nmfenzu；

Datalines；

Input I_280nm I_300nm I_332nmFenzu data ...

Proc Logistic data=dataset name；

Model fenzu=I_280nm I_300nm I_332nm/Rsq Lackfit；

Run；

4, the accuracy of discrimination formula is verified

The accuracy differentiating that fuel oil and the crude oil of marine oil overflow are differentiated by model to verify the oil that the present invention sets up to plant, By above-mentioned 30 days air slaking market demands of 34 kinds of oil samples in above-mentioned formula, carrying out binary Logistic regression diagnostics, crude oil differentiates standard Really rate reaches 95.4%, and fuel oil differentiates rate of accuracy reached 91.7%.

In following embodiment, fluorescent intensity uses molecular fluorescence spectrometry to measure, and selected instrument is as follows with method:

Instrument and reagent: analytical tool is Cary Eclipse type Fluorescence spectrophotometer (Varian company of the U.S.)；

Solvent: normal hexane (chromatographically pure, Germany Merck)；

Permanent wavelength method is used to be measured, the condition of scanning: Δ λ=10nm；

Sample pre-treatments: weigh 0.05g sample oil with beaker, is dissolved in 10ml normal hexane by acquired oil sample, and concussion is extremely It is completely dissolved, more static 5 minutes, pipettes 40ul supernatant in test tube, add 10ml normal hexane, continue to employ to be measured.

Embodiment 1: with the Daqing crude oil checking before and after air slaking

Table 1: non-air slaking Daqing crude oil fluorescence intensity under 3 characteristic wavelengths

λ/nm	280±2	300±2	332±2
				I/a.u.	110.86	112.20	150.54

Fluorescence intensity level in table 1 is brought into above-mentioned y computing formula:

Y=-24.39+0.46I_280nm-0.50I_300nm+0.12I_332nm=-11.94

Pass through againCalculate: π=0.00 < 0.5, illustrate that this oil sample is crude oil, meet with known case.

Table 2: the 30 days Daqing crude oils of air slaking fluorescence intensity under 3 characteristic wavelengths

λ/nm	280±2	300±2	332±2
				I/a.u.	98.04	96.79	111.46

Fluorescence intensity level in table 2 is brought into above-mentioned y computing formula:

Y=-24.39+0.46I_280nm-0.50I_300nm+0.12I_332nm=-14.78

Pass through againCalculate: π=0.00 < 0.5, illustrate that this oil sample is crude oil, meet with known case.

Embodiment 2: with Oman's crude oil checking before and after air slaking

Table 3: non-air slaking Oman crude oil fluorescence intensity under 3 characteristic wavelengths

λ/nm	280±2	300±2	332±2
				I/a.u.	124.99	119.98	162.22

Fluorescence intensity level in table 3 is brought into above-mentioned y computing formula:

Y=-24.39+0.46I_280nm-0.50I_300nm+0.12I_332nm=-7.99

Pass through againCalculate: π=0.00 < 0.5, illustrate that this oil sample is crude oil, meet with known case.

Table 4: the 30 days Oman's crude oil of air slaking fluorescence intensity under 3 characteristic wavelengths

λ/nm	280±2	300±2	332±2
				I/a.u.	136.83	134.07	188.39

Fluorescence intensity level in table 4 is brought into above-mentioned y computing formula:

Y=-24.39+0.46I_280nm-0.50I_300nm+0.12I_332nm=-9.10

Pass through againCalculate: π=0.00 < 0.5, illustrate that this oil sample is crude oil, meet with known case.

Embodiment 3: with light-weight fuel oil checking before and after air slaking

Table 5: non-air slaking light-weight fuel oil fluorescence intensity under 3 characteristic wavelengths

λ/nm	280±2	300±2	332±2
				I/a.u.	238.87	276.88	475.28

Fluorescence intensity level in table 5 is brought into above-mentioned y computing formula:

Y=-24.39+0.46I_280nm-0.50I_300nm+0.12I_332nm=2.99

Pass through againCalculate: π=0.95 0.5, illustrate that this oil sample is fuel oil, meet with known case.

Table 6: the 30 days light-weight fuel oils of air slaking fluorescence intensity under 3 characteristic wavelengths

λ/nm	280±2	300±2	332±2
				I/a.u.	227.82	260.54	463.37

Fluorescence intensity level in table 6 is brought into above-mentioned y computing formula:

Y=-24.39+0.46I_280nm-0.50I_300nm+0.12I_332nm=4.71

Pass through againCalculate: π=0.99 0.5, illustrate that this oil sample is fuel oil, meet with known case.

Embodiment 4: with heavy oil checking before and after air slaking

Table 7: non-air slaking heavy oil fluorescence intensity under 3 characteristic wavelengths

λ/nm	280±2	300±2	332±2
				I/a.u.	255.96	228.98	252.18

Fluorescence intensity level in table 7 is brought into above-mentioned y computing formula:

Y=-24.39+0.46I_280nm-0.50I_300nm+0.12I_332nm=7.94

Pass through againCalculate: π=1.00 0.5, illustrate that this oil sample is fuel oil, meet with known case.

Table 8: the 30 days heavy oils of air slaking fluorescence intensity under 3 characteristic wavelengths

λ/nm	280±2	300±2	332±2
				I/a.u.	252.10	218.98	241.62

Fluorescence intensity level in table 8 is brought into above-mentioned y computing formula:

Y=-24.39+0.46I_280nm-0.50I_300nm+0.12I_332nm=9.92

Pass through againCalculate: π=1.00 0.5, illustrate that this oil sample is fuel oil, meet with known case.

Claims (3)

1. fluorescence method rapid qualitative differentiates fuel oil and the method for crude oil of marine oil overflow, it is characterised in that: comprise the steps:

1. testing sample fluorescence intensity level under 280 ± 2nm, 300 ± 2nm and 332 ± 2nm characteristic wavelength is obtained；

2. the fluorescence intensity level under three characteristic wavelengths step 1. obtained is brought in following formula,

$\mathrm{\&pi;}=\frac{e^y}{1+e^y}$

Wherein, y=-24.39+0.46I_280nm-0.50I_300nm+0.12I_332nm,

Wherein, I_280nmIt is characterized the fluorescence intensity under wavelength 280 ± 2nm；I_300nmThe fluorescence being characterized under wavelength 300 ± 2nm is strong Degree；I_332nmIt is characterized the fluorescence intensity under wavelength 332 ± 2nm；

When π ∈ [0,0.5), institute's test sample product are crude oil；When π ∈ (0.5,1], institute's test sample product are fuel oil.

Method the most according to claim 1, it is characterised in that: the fluorescence intensity level of described sample utilizes permanent wavelength method to survey Fixed.

Method the most according to claim 1 and 2, it is characterised in that: the fluorescence intensity level of described sample is glimmering by molecule Light spectrophotometer records.