Model Construction for Soil Styrene Pollution Prediction Based on Infrared Spectroscopy

Tianyou Hu; Zhili Chen; Jin Tang; Haowen Wang; Jialian Ning

doi:10.3788/AOS202040.0830001

Acta Optica Sinica, Volume. 40, Issue 8, 0830001(2020)

Model Construction for Soil Styrene Pollution Prediction Based on Infrared Spectroscopy

Tianyou Hu, Zhili Chen^*, Jin Tang, Haowen Wang, and Jialian Ning

Author Affiliations

College of Environmental Science and Engineering, Guilin University of Technology, Guilin, Guangxi 541006, China

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Figures & Tables(7)

Fig. 1. Spectral curves of different styrene contaminated soils. (a) Brick laterite; (b) black soil; (c) purple soil; (d) uncontaminated soil

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Fig. 2. Spectral curves of different styrene contaminated soils after continuum removal processing. (a1)(b1)(c1) Feature band is located at 1800 nm; (a2)(b2)(c2) feature band is located at 2200 nm and 2400 nm

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Fig. 3. Styrene contents in three soils predicted by different models. (a) Styrene-brick laterite; (b) styrene-black soil; (c) styrene-purple soil

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Table 1. Physical and chemical properties of tested soils

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Table 1. Physical and chemical properties of tested soils

Soil type	Sampled area	pH	Organic matter content/(g·kg^-1)	Soil texture	Volume fraction /%
Soil type	Sampled area	pH	Organic matter content/(g·kg^-1)	Soil texture	Clay	Silt	Sand
Brick laterite	Haikou, Hainan	6.0	6.18	Sandy loam	17.65	25.43	56.92
Black soil	Hulunbeir, Inner Mongolia	7.2	46.55	Clay loam	20.36	38.19	41.45
Purple soil	Beibei, Chongqing	7.9	12.92	Loamy clay	33.41	43.91	22.68

Table 2. Sample number and saturation content of soil and hydrocarbons
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Table 2. Sample number and saturation content of soil and hydrocarbons
Soil type Number of samples Initial addition volume /mL Variable node /mL Subsequent addition volume /mL Saturation value /mL
Brick laterite 20 0.5 4.0 1.0 6.0
Black soil 20 0.5 5.0 1.0 5.0
Purple soil 20 0.2 2.4 0.4 3.6

Table 3. Correlation coefficients of styrene in each characteristic band under different transformation forms of spectral reflectance of brick laterite

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Table 3. Correlation coefficients of styrene in each characteristic band under different transformation forms of spectral reflectance of brick laterite

Characteristicband /nm	R	1/R	ln(1/R)	1/ln(R)	R'	(1/R)'	ln(1/R)'	(1/ln R)'
1766	-0.9557	0.9960	0.9816	0.9414	0.0607	0.6514	-0.2103	0.3356
1809	-0.9555	0.9967	0.9823	0.9367	0.6241	-0.4953	-0.6673	-0.5506
1884	-0.9598	0.9955	0.9825	0.9459	-0.6861	-0.7487	0.7847	-0.1121
1913	-0.9462	0.9966	0.9793	0.9353	0.1873	-0.6094	-0.1122	-0.4585
2119	-0.9363	0.9961	0.9758	0.9160	0.2428	0.7118	-0.4364	0.3616
2173	-0.9345	0.9978	0.9791	0.9239	-0.9121	0.7536	0.8734	0.9760
2200	-0.9393	0.9992	0.9815	0.9332	-0.5970	0.1536	0.6146	0.4241
2278	-0.9317	0.9987	0.9785	0.9232	0.6191	-0.8906	-0.6205	-0.8189
2348	-0.9333	0.9988	0.9799	0.9290	-0.3957	-0.6741	0.4209	-0.3047
2387	-0.9402	0.9993	0.9833	0.9369	-0.4601	-0.2115	0.4763	0.0882
2464	-0.9091	0.9986	0.9738	0.9141	-0.2321	-0.7170	0.1297	-0.5027

Table 4. Accuracy comparison and prediction verification among different models

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Table 4. Accuracy comparison and prediction verification among different models

Soil type	Model type	Model building		Model prediction
Soil type	Model type	$R_{1}^{2}$	RMSEC	$R_{1}^{2}$	RMSEP
Brick laterite	SMLR	0.9986	0.10906	0.9966	0.11188
	PLSR	0.9977	0.08871	0.9986	0.07520
	SVMR	0.9844	0.23338
Black soil	SMLR	0.9979	0.10842	0.9946	0.11257
	PLSR	0.9823	0.20247	0.9793	0.21859
	SVMR	0.9644	0.28913
Purple soil	SMLR	0.9986	0.05347	0.9957	0.08226
	PLSR	0.9921	0.08928	0.9928	0.08583
	SVMR	0.9860	0.12311

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Tianyou Hu, Zhili Chen, Jin Tang, Haowen Wang, Jialian Ning. Model Construction for Soil Styrene Pollution Prediction Based on Infrared Spectroscopy[J]. Acta Optica Sinica, 2020, 40(8): 0830001

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