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Estimation of Potentially Toxic Elements Contamination in Anthropogenic Soils on a Brown Coal Mining Dumpsite by Reflectance Spectroscopy: A Case Study

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  • Asa Gholizadeh
  • Luboš Borůvka
  • Radim Vašát
  • Mohammadmehdi Saberioon
  • Aleš Klement
  • Josef Kratina
  • Václav Tejnecký
  • Ondřej Drábek

Abstract

In order to monitor Potentially Toxic Elements (PTEs) in anthropogenic soils on brown coal mining dumpsites, a large number of samples and cumbersome, time-consuming laboratory measurements are required. Due to its rapidity, convenience and accuracy, reflectance spectroscopy within the Visible-Near Infrared (Vis-NIR) region has been used to predict soil constituents. This study evaluated the suitability of Vis-NIR (350–2500 nm) reflectance spectroscopy for predicting PTEs concentration, using samples collected on large brown coal mining dumpsites in the Czech Republic. Partial Least Square Regression (PLSR) and Support Vector Machine Regression (SVMR) with cross-validation were used to relate PTEs data to the reflectance spectral data by applying different preprocessing strategies. According to the criteria of minimal Root Mean Square Error of Prediction of Cross Validation (RMSEPcv) and maximal coefficient of determination (R2cv) and Residual Prediction Deviation (RPD), the SVMR models with the first derivative pretreatment provided the most accurate prediction for As (R2cv) = 0.89, RMSEPcv = 1.89, RPD = 2.63). Less accurate, but acceptable prediction for screening purposes for Cd and Cu (0.66 ˂ R2cv) ˂ 0.81, RMSEPcv = 0.0.8 and 4.08 respectively, 2.0 ˂ RPD ˂ 2.5) were obtained. The PLSR model for predicting Mn (R2cv) = 0.44, RMSEPcv = 116.43, RPD = 1.45) presented an inadequate model. Overall, SVMR models for the Vis-NIR spectra could be used indirectly for an accurate assessment of PTEs’ concentrations.

Suggested Citation

  • Asa Gholizadeh & Luboš Borůvka & Radim Vašát & Mohammadmehdi Saberioon & Aleš Klement & Josef Kratina & Václav Tejnecký & Ondřej Drábek, 2015. "Estimation of Potentially Toxic Elements Contamination in Anthropogenic Soils on a Brown Coal Mining Dumpsite by Reflectance Spectroscopy: A Case Study," PLOS ONE, Public Library of Science, vol. 10(2), pages 1-14, February.
  • Handle: RePEc:plo:pone00:0117457
    DOI: 10.1371/journal.pone.0117457
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    References listed on IDEAS

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    1. Mevik, Björn-Helge & Wehrens, Ron, 2007. "The pls Package: Principal Component and Partial Least Squares Regression in R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 18(i02).
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    1. Asa Gholizadeh & Luboš Borůvka & Mohammad Mehdi Saberioon & Josef Kozák & Radim Vašát & Karel Němeček, 2015. "Comparing different data preprocessing methods for monitoring soil heavy metals based on soil spectral features," Soil and Water Research, Czech Academy of Agricultural Sciences, vol. 10(4), pages 218-227.
    2. Hyeongyu Lee & Yosoon Choi & Jangwon Suh & Seung-Ho Lee, 2016. "Mapping Copper and Lead Concentrations at Abandoned Mine Areas Using Element Analysis Data from ICP–AES and Portable XRF Instruments: A Comparative Study," IJERPH, MDPI, vol. 13(4), pages 1-15, March.

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