Feasibility of Reflectance Spectroscopy for the Assessment of Soil Mercury Contamination

Abstract

Conventional methods for investigating soil Hg contamination based on raster sampling and chemical analysis are time-consuming and relatively expensive. The objective of this study was to develop a rapid method for investigating Hg concentration in suburban agricultural soils of the Nanjing region using reflectance spectra within the visible-near-infrared (VNIR) region. Several spectral pretreatments (absorbance, Kubelka-Munk transformations and their derivatives) were applied to the reflectance spectra to optimize the accuracy of prediction. The prediction of Hg concentration was achieved by univariate regression and principal component regression (PCR) approaches. The optimal model (R= 0.69, RMSEP = 0.15) for predicting Hg was achieved using the PCR method with the Kubelka-Munktransformation asthe spectral predictor. Comparison of three wavelength ranges (0.38-1.1, 1.0-2.5, and 0.38-2.5 microm) on the effect of prediction accuracy showed that the best results were acquired using the 1.0-2.5 microm spectral region. Correlation analysis revealed that Hg concentration was negatively correlated with soil reflectance while positively correlated with the absorption depths of goethite at 0.496 microm and clay minerals at 2.21 microm, suggesting that Hg-sorption by clay-size mineral assemblages in soils was the mechanism by which to predict spectrally featureless Hg. These results indicate that it is feasible to predict Hg levels in agricultural soils using the rapid and cost-effective reflectance spectroscopy. Future study with operational remote sensing techniques and field measurements is strongly recommended.

Monitoring plant response to phenanthrene using the red edge of canopy hyperspectral reflectance

“…The monitoring of affected vegetation uses various methods such as sampling and chemical analysis of the soil, water, air and plants (Manzo et al, 2013;Nascimbene et al, 2014). However, these ground-based methods are time-consuming and expensive, especially when they are applied to large areas (Wu et al, 2005;Yi et al, 2007;Fauzi et al, 2013). Airborne or spaceborne remote sensing can simultaneously monitor relatively large areas quickly in a non-destructive fashion and could be integrated with a field-based approach, improving monitoring ability (Ayanu et al, 2012;Hunter et al, 2009).…”

Near-Infrared Spectroscopy Combined with Multivariate Tools for Analysis of Trace Metals in Environmental Matrices

“…For instance, the absorption features associated with electronic transitions of Fe 3+ and Fe 2+ ions in Fe-bearing minerals can be found in the near-infrared region at 780-1200 nm [33][34][35]. In addition, the absorption features of metals associated with molecular vibrations of organic and inorganic functional groups in organic matter, silicates, carbonates, and water can be found in near infrared at 780-2500 nm region [24,33,34,36].…”

“…Wu et al [24,36] reported the feasibility of using NIRS for monitoring and predicting trace metals in suspended solids, sediment, and soil. This was achieved by quantitative evaluations of the spectral activity of sediment and soil properties [23][24][25][26][27][28][29][30][31][32][33][34][35][36][37].…”

“…This was achieved by quantitative evaluations of the spectral activity of sediment and soil properties [23][24][25][26][27][28][29][30][31][32][33][34][35][36][37]. However, due to challenges such as the collinearity, band overlaps, and interactions for some soil properties, the spectra of soil, sediment, or suspended solids are often broad and nonspecific [25].…”

“…Wu et al [36] reported the practicality of using NIRS for the determination of Hg concentration agricultural soil samples. The accuracy of the prediction models was optimized by applying several spectral pretreatments to the reflectance spectra.…”