Estimating heavy metal concentrations in suburban soils with reflectance spectroscopy

• Published in: Geoderma Vol. 336; pp. 59 - 67
• Main Authors: Cheng, Hang, Shen, Ruili, Chen, Yiyun, Wan, Qijin, Shi, Tiezhu, Wang, Junjie, Wan, Yuan, Hong, Yongsheng, Li, Xiaocui
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 15.02.2019
• Subjects: arsenic; cadmium; China; chromium; copper; Estimation mechanism; heavy metals; iron; lead; monitoring; Partial correlation analysis; PCA biplot analysis; reflectance; reflectance spectroscopy; remediation; soil; Soil heavy metal; soil organic matter; soil pollution; soil sampling; suburban areas; VNIR spectroscopy; zinc; China; PCA biplot analysis; Soil heavy metal; Estimation mechanism; VNIR spectroscopy; Partial correlation analysis
• DOI: 10.1016/j.geoderma.2018.08.010
• ISSN: 0016-7061

Soil contamination by heavy metals has become a serious environmental issue worldwide. Rapidly and reliably obtaining heavy metal concentrations in soil is vital for soil monitoring and remediation. Visible and near-infrared reflectance (VNIR) spectroscopy provides a promising method for the estimation of heavy metal concentrations over large areas. Ninety-three soil samples were collected from a suburb of Wuhan City, Hubei Province, China, and their reflectance spectra were measured in the laboratory. This study aimed to (i) examine the feasibility of using soil reflectance spectra to estimate the concentrations of Cd, Pb, As, Cr, Cu and Zn in suburban soils; (ii) compare the performances of different spectral pretreatments and (iii) explore the mechanism underlying the estimation of heavy metal concentration from VNIR spectra. In particular, we proposed a strategy for the mechanism investigation that combined PCA biplot analysis, correlation and partial correlation analyses. Partial least-square regression was adopted to calibrate the VNIR model. Results showed that the VNIR model provided acceptable estimation accuracies for Cr, As and Cd concentrations with the ratio of the performance to deviation (RPD) values of 2.70, 1.81 and 1.63, respectively, but unsatisfactory estimation accuracies for Pb, Cu and Zn concentrations with the RPD values of 0.70–1.03. Savitzky–Golay smoothing outperformed other spectral pretreatments. The mechanisms underlying the estimation of the six studied heavy metals varied on a case-to-case basis. Specifically, the spectral estimation of Cd (Group I) concentration was attributed to its close correlations with soil organic matter (SOM). Cr and As (Group II) concentrations could be estimated by the VNIR model on the basis of their close correlations with Fe. Pb, Cu and Zn (Group III) concentrations, however, had weak correlations with neither SOM nor Fe, resulting in poor estimations. The proposed strategy on mechanism investigation for heavy metals could be transferred to other study areas. In summary, VNIR spectroscopy combined with the PLSR model is an alternative method for the rapid monitoring of some heavy metal pollution in suburban soils. [Display omitted] •VNIR spectroscopy can accurately estimate Cr concentrations in suburban soils.•We propose a comprehensive analytical framework to investigate the mechanism.•The framework involved PCA biplot, correlation and partial correlation analysis.•Estimation mechanism of Cd was attributed to its close correlation with SOM.•Estimation mechanism of As and Cr may ascribe to the close correlations with Fe.