Establishment of quantitative detection model for heavy metals insoil using portable X-ray fluorescence spectrometerbased on algorithm optimization
JIANG Xiaoyu1,2, LI Fusheng*1,2, WANG Qingya1,2LUO Jie3, HAO Jun1,2, XU Muqiang2
1. Engineering Research Center of Nuclear Technology Application, Ministry of Education, East China University of Technology, Nanchang 330013, China;
2. State Key Laboratory of Nuclear Resources and Environment, East China University of Technology, Nanchang 330013, China;
3. Yangtze University, Wuhan 430000, China
Combining wavelet transform denoising with iterative polynomial fitting to remove background, the spectra of portable X-ray fluorescence (PXRF) were treated with noise removal and background deduction. Then the standard curve of each heavy metal was established according to the standard value of soil heavy metal content and the counting rate measured after treatment. Compared to the method without noise removal and background deduction, the determination coefficient (R2) range of the standard curve after sym4 wavelet denoising and 9 times iterative polynomial fitting were improved to 0.965 2-0.998 5, which effectively improved the accuracy and precision of the instrument detection. Moreover, the contents of six heavy metal elements (including copper, arsenic, chromium, zinc, lead and nickel) in soil samples were determined using PXRF with and without algorithm optimization (wavelet transform denoising iterative polynomial fitting). The detection limit, accuracy and precision were compared and analyzed. The results showed that: in terms of accuracy, the relative error range before algorithm optimization were 0.2%-4.8%, and it was improved to 0.4%-4.6% after algorithm optimization treatment; in terms of precision, the relative standard deviation range was 0.50%-5.2% after algorithm optimization, while it was 0.80%-15% before algorithm optimization; in terms of detection limit, the detection limits of 6 heavy metals were reduced to 3.5-22.0 μg/g after algorithm processing. Finally, compared with the laboratory test results, the data showed that the results of some elements could be close to the laboratory analysis standard, and the experimental results have no significant difference. The testing results were comparable. The proposed method could be used for large area soil environmental remediation and environmental monitoring.
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