Rapid Quantification of Heavy Metals in Oil Sludge Based on Laser-Induced Breakdown Spectroscopy Combined with Random Forest Algorithm
Journal Title: Chinese Journal of Inorganic Analytical Chemistry - Year 2025, Vol 15, Issue 6
Abstract
The quantitative analysis of heavy metal elements in oily sludge is of great significance for the assessment of soil environmental pollution in petroleum and petrochemical industrial areas. In this study，the laser-induced breakdown spectroscopy (LIBS) spectra of 30 oil-containing sludge samples in the 200-500 nm band were acquired using a LIBS spectrometer，and the initial random forest (RF) calibration model was established based on the original LIBS spectra for the quantitative analysis of Cu，Cr，and Pb in oil sludge. Subsequently，the impacts of 4 preprocessing methods (normalization (Nor)，multivariate scattering correction (MSC)，first derivative (D1st)，and second derivative (D2nd)) on the quantitative analysis of Cu，Cr，and Pb in oil sludge were explored. On this foundation，the pre-processed LIBS spectral data were employed as the initial input variables to construct the RF calibration model based on variable importance measures (VIM)，and the variable importance thresholds were optimized through out-of-bag error estimation. Finally，the optimal RF calibration model was constructed based on the optimized threshold and variables. The results indicated that the optimal coefficients of determination (R2) of the optimized model for the prediction sets of Cu，Cr，and Pb were 0.980 1，0.971 3，and 0.973 6 respectively，and the optimal root mean square error (RMSE) was 0.023 5，0.028 3，and 0.025 2 mg/kg respectively. This research can offer some theoretical and technical references for the environmental risk monitoring of heavy metals in oil sludge in petroleum and petrochemical industrial areas.
Authors and Affiliations
Maogang LI, Kui ZHOU, Yan XING, Qi CAI, Chunhua YAN, Tianlong ZHANG, Yao DU, Hua LI
Keywords
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- EP ID EP767889
- DOI 10.20236/j.CJIAC.2025.06.003
- Views 10
- Downloads 0
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