Heavy metal pollution at mine sites estimated from reflectance spectroscopy following correction for skewed data.

The heavy metal concentration of soil samples often exhibits a skewed distribution, especially for soil samples from mining areas with an extremely high concentration of heavy metals. In this study, to model soil contamination in mining areas using reflectance spectroscopy, the skewed distribution was corrected and heavy metal concentration estimated. In total, 46 soil samples from a mining area, along with corresponding field soil spectra, were collected. Laboratory spectra of the soil samples and the field spectra were used to estimate copper (Cu) concentration in the mining area. A logarithmic transformation was used to correct the skewed distribution, and based on the sorption of Cu on spectrally active soil constituents, the spectral bands associated with iron oxides were extracted from the visible and near-infrared (VNIR) region and used in the estimation. A genetic algorithm was adopted for band selection, and partial least squares regression was used to calibrate the estimation model. After transforming the distribution of Cu concentration, the accuracies (R2) of the estimation of Cu concentration using laboratory and field spectra separately were 0.94 and 0.96. The results indicate that Cu concentration in the mining area can be estimated using reflectance spectroscopy following correction of skewed distribution.

[1]  Wouter Saeys,et al.  Potential for Onsite and Online Analysis of Pig Manure using Visible and Near Infrared Reflectance Spectroscopy , 2005 .

[2]  M. L. Andrade,et al.  Competitive sorption and desorption of heavy metals in mine soils: influence of mine soil characteristics. , 2006, Journal of colloid and interface science.

[3]  Xia Zhang,et al.  Predicting nickel concentration in soil using reflectance spectroscopy associated with organic matter and clay minerals , 2018, Geoderma.

[4]  Chen Huamain,et al.  HEAVY METAL POLLUTION IN SOILS IN CHINA : STATUS AND COUNTERMEASURES , 1999 .

[5]  A. McBratney,et al.  Critical review of chemometric indicators commonly used for assessing the quality of the prediction of soil attributes by NIR spectroscopy , 2010 .

[6]  E. R. Stoner,et al.  Characteristic variations in reflectance of surface soils , 1981 .

[7]  S. Wold,et al.  The multivariate calibration problem in chemistry solved by the PLS method , 1983 .

[8]  M. Vohland,et al.  Comparing different multivariate calibration methods for the determination of soil organic carbon pools with visible to near infrared spectroscopy , 2011 .

[9]  R. V. Rossel,et al.  Visible, near infrared, mid infrared or combined diffuse reflectance spectroscopy for simultaneous assessment of various soil properties , 2006 .

[10]  Xia Zhang,et al.  Estimating soil zinc concentrations using reflectance spectroscopy , 2017, Int. J. Appl. Earth Obs. Geoinformation.

[11]  Mohammadmehdi Saberioon,et al.  Estimation of Potentially Toxic Elements Contamination in Anthropogenic Soils on a Brown Coal Mining Dumpsite by Reflectance Spectroscopy: A Case Study , 2015, PloS one.

[12]  Yaolin Liu,et al.  Feasibility of Estimating Cu Contamination in Floodplain Soils using VNIR Spectroscopy—A Case Study in the Le’an River Floodplain, China , 2012 .

[13]  Lutgarde M. C. Buydens,et al.  The potential of field spectroscopy for the assessment of sediment properties in river floodplains , 2003 .

[14]  Tiezhu Shi,et al.  Prediction of low heavy metal concentrations in agricultural soils using visible and near-infrared reflectance spectroscopy , 2014 .

[15]  H. Bradl.  Adsorption of heavy metal ions on soils and soils constituents. , 2004, Journal of colloid and interface science.

[16]  Xia Zhang,et al.  Exploring the Potential of Spectral Classification in Estimation of Soil Contaminant Elements , 2017, Remote. Sens..

[17]  R. Leardi,et al.  Genetic algorithms applied to feature selection in PLS regression: how and when to use them , 1998 .

[18]  Guofeng Wu,et al.  Visible and near-infrared reflectance spectroscopy-an alternative for monitoring soil contamination by heavy metals. , 2014, Journal of hazardous materials.

[19]  Tao Chen,et al.  Rapid identification of soil cadmium pollution risk at regional scale based on visible and near-infrared spectroscopy. , 2015, Environmental pollution.

[20]  Alejandro C. Olivieri,et al.  A new family of genetic algorithms for wavelength interval selection in multivariate analytical spectroscopy , 2003 .

[21]  Abdul Mounem Mouazen,et al.  Special issue ‘Diffuse reflectance spectroscopy in soil science and land resource assessment’ , 2010 .

[22]  Zhihao Qin,et al.  Possibilities of reflectance spectroscopy for the assessment of contaminant elements in suburban soils , 2005 .

[23]  A. Savitzky,et al.  Smoothing and Differentiation of Data by Simplified Least Squares Procedures. , 1964 .

[24]  M. L. Andrade,et al.  Simultaneous sorption and desorption of Cd, Cr, Cu, Ni, Pb, and Zn in acid soils II. Soil ranking and influence of soil characteristics. , 2007, Journal of hazardous materials.

[25]  Hang Cheng,et al.  Estimating heavy metal concentrations in suburban soils with reflectance spectroscopy , 2019, Geoderma.

[26]  L. Zhenhua,et al.  Analysis on pollution of heavy metal in Shuikoushan Pb-Zn mining and smelting area in Hengyang , 2012 .

[27]  M. L. Andrade,et al.  Competitive sorption and desorption of heavy metals by individual soil components. , 2007, Journal of hazardous materials.

[28]  Tibor Németh,et al.  Association of individual soil mineral constituents and heavy metals as studied by sorption experiments and analytical electron microscopy analyses. , 2009, Journal of hazardous materials.

[29]  P. Rathod,et al.  Proximal Spectral Sensing to Monitor Phytoremediation of Metal-Contaminated Soils , 2013, International journal of phytoremediation.

[30]  Edward V. Thomas,et al.  A primer on multivariate calibration , 1994 .

[31]  Lutgarde M. C. Buydens,et al.  Possibilities of visible–near-infrared spectroscopy for the assessment of soil contamination in river floodplains , 2001 .

[32]  L. Buydens,et al.  Exploring field vegetation reflectance as an indicator of soil contamination in river floodplains. , 2004, Environmental pollution.

[33]  Alex B. McBratney,et al.  Laboratory evaluation of a proximal sensing technique for simultaneous measurement of soil clay and water content , 1998 .

[34]  Peng Gong,et al.  A mechanism study of reflectance spectroscopy for investigating heavy metals in soils , 2007 .

[35]  Xia Zhang,et al.  Predicting cadmium concentration in soils using laboratory and field reflectance spectroscopy. , 2019, The Science of the total environment.

[36]  Michael Vohland,et al.  A spectroscopic approach to assess trace–heavy metal contents in contaminated floodplain soils via spectrally active soil components , 2009 .

[37]  R. Clark,et al.  Reflectance spectroscopy: Quantitative analysis techniques for remote sensing applications , 1984 .