Visible and near-infrared reflectance spectroscopy—An alternative for monitoring soil contamination by heavy metals

Shi, Tiezhu; Chen, Yiyun; Liu, Yanfang; Wu, Guofeng

doi:10.1016/j.jhazmat.2013.11.059

Cited by 281 publications

(147 citation statements)

References 90 publications

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“…The parent material in Qatar soils is dominated by dolomite and limestone and normally has very low organic matter, clay and iron contents [38], and the toxic metals' concentrations in Qatar soils are generally low. Therefore, it would be difficult to capture spectral features of toxic metals directly from the soils, even though most of the soil in Qatar is bare [26,27,29,32,36,65].…”

Section: Seasonal Dependency On Soil Toxic Metals' Determinationmentioning

confidence: 99%

“…Melendez-Pastor et al [25] comprehensively reviewed the role of RS in soil toxic metals' detection and found it to be an efficient tool for detecting sources of toxic metals' contamination in soils. This is despite the fact that toxic metals in soils appear in low or moderate concentrations (e.g., Cr and Cu <4000 mg·kg −1 ) and are spectrally featureless, although they can easily bind to minerals and organic matter [26][27][28]. Especially the reflectance spectral information of minerals in soils plays an important role in predicting toxic metals because the spectral assignments' position of minerals can change with their chemical composition and surface activity [27,[29][30][31][32].…”

Section: Introductionmentioning

confidence: 99%

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Digital Mapping of Toxic Metals in Qatari Soils Using Remote Sensing and Ancillary Data

Kheir

Adhikari

et al. 2016

Remote Sensing

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After decades of mining and industrialization in Qatar, it is important to estimate their impact on soil pollution with toxic metals. The study utilized 300 topsoil (0-30 cm) samples, multi-spectral images (Landsat 8), spectral indices and environmental variables to model and map the spatial distribution of arsenic (As), chromium (Cr), nickel (Ni), copper (Cu), lead (Pb) and zinc (Zn) in Qatari soils. The prediction model used condition-based rules generated in the Cubist tool. In terms of R 2 and the ratio of performance to interquartile distance (RPIQ), the models showed good predictive capabilities for all elements. Of all of the prediction results, Cu had the highest R 2 = 0.74, followed by As > Pb > Cr > Zn > Ni. This study found that all of the models only chose images from January and February as predictors, which indicates that images from these two months are important for soil toxic metals' monitoring in arid soils, due to the climate and the vegetation cover during this season. Topsoil maps of the six toxic metals were generated. The maps can be used to prioritize the choice of remediation measures and can be applied to other arid areas of similar environmental/socio-economic conditions and pollution causes.

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Section: Seasonal Dependency On Soil Toxic Metals' Determinationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Digital Mapping of Toxic Metals in Qatari Soils Using Remote Sensing and Ancillary Data

Kheir

Adhikari

et al. 2016

Remote Sensing

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“…Multiple linear regression (MLR) is a conventional chemometric method that commonly correlates a linear combination of several selected spectral bands/indices which have high correlations with the heavy metal concentrations [18]. The disadvantage of using MLR is that it does not perform well with hyperspectral measurements.…”

Section: Applications Of Nirs-multi-linear Regression Determination Tmentioning

confidence: 99%

“…The disadvantage of using MLR is that it does not perform well with hyperspectral measurements. This is because the NIR spectral data usually exhibit high collinearity [18,39]. This challenge has been solved by applying the enter and stepwise MLR approaches [18,39].…”

Section: Applications Of Nirs-multi-linear Regression Determination Tmentioning

confidence: 99%

“…Therefore, a rapid, reliable, and environmentally friendly method is required to detect and survey the distribution of trace metals in environmental matrices. This is done in order to diagnose suspected contaminated areas as well as control the rehabilitation processes [18]. Reflectance spectroscopy is the study of the absorption and emission of light and other radiations by matter as related to the dependence of these processes on the wavelength of the radiation [19].…”

Section: Introductionmentioning

confidence: 99%

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

Nomngongo¹,

Munonde²,

Mpupa³

et al. 2017

Developments in Near-Infrared Spectroscopy

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Environmental contamination by trace elements is becoming increasingly important problem worldwide. Trace metals such as cadmium, copper, lead, chromium, and mercury are major environmental pollutants that are predominantly found in areas with high anthropogenic activities. Therefore, there is a need for rapid and reliable tools to assess and monitor the concentration of heavy metal in environmental matrices. A nondestructive, cost-effective, and environmentally friendly procedure based on near-infrared reflectance spectroscopy (NIRS) and chemometric tools has been used as alternative technique for the simultaneous estimation of various heavy metal concentrations in environmental sample. The metal content is estimated by assigning the absorption features of metals associated with molecular vibrations of organic and inorganic functional groups in organic matter, silicates, carbonates, and water at 780-2500 nm in the near-infrared region.This chapter, reviewed the application of NIRS combined with chemometric tools such as multiple linear regression (MLR), principal component regression (PCR), and partial least squares (PLS) regression. The disadvantages and advantages of each chemometric tool are discussed briefly.

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Short‐Wave Infrared Chip‐Spectrometer by Using Laser Direct‐Writing Grayscale Lithography

Xuan

Wang

Liu

et al. 2022

Advanced Optical Materials

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Short-wave infrared (SWIR) spectrometer has been a critical device in spectral analysis fields like agriculture, [1,2] environmental monitoring, [3] astronomy, [4,5] etc. Conventionally, the infrared spectrometer is bulky and delicate due to the spectral division device, such as grating and prism, which limited its applications. The demand and potential for compact spectrometers are enormous for portable and on-chip applications like smartphone spectrometer, [6,7] hyperspectral imaging, [8][9][10] etc. The key to miniaturizing spectrometers is replacing the bulky spectral split devices with miniature photonic devices. [11] Besides, combing with reconstruction algorithms such as compressed sensing and machine learning, the incident light spectrum can be reconstructed with a few numbers of filters. [8,[12][13][14] In recent years, such reconstructive micospectrometer based on Si-based complementary metal-oxide-semiconductor (CMOS) sensors in visible range are primarily investigated. In comparison, the microspectrometer in SWIR range is much more useful to acquire object information in practical applications. Strategies based on photonic devices slab, [9,10,[15][16][17][18][19] quantum dot (QD) slab, [20][21][22] nanowire, [23,24] have been proposed for portable and on-chip microspectrometer. The number and variety of filter spectra determined the resolution of reconstructive microspectrometer. Micro-nano photonic device filters like photonic crystal (PC), metamaterial, Fabry-Perot (FP) cavities can acquire distinctive spectra by varying structure morphology parameters. Material-based filters like QD slab can acquire different spectra by adjusting their size, composition, or bias. Those filters mentioned above are usually fabricated onto a separated slab and then pasted or bonded with a detector chip. In practical applications, the separated slab is fragile and difficult to well-matching with detector pixels, leading to spectral crosstalk and other problems. Recently proposed detector-only reconstructive microspectrometer based on nanowires, [23,24] black phosphorus [25] is ultra-compact without external filters. It has a stable structure with wavelength scale size, but the number of response spectra is hard to increase significantly and limits its resolution.Among these micro-nano filters, FP microcavities array has low spectral correlation coefficient by varying its cavity length, Short-wave infrared (SWIR) information is critical for material analysis, imaging sensing, and other fields. To acquire SWIR spectrum with compact devices, strategies for reconstructive microspectrometer have emerged, such as photonic crystal and quantum dot filter. However, the current SWIR microspectrometer needs many filters with insufficient resolution. In this work, the authors develop a SWIR chip-spectrometer based on Fabry-Perot microcavities array which can be fabricated by using fast and low-cost UV laser directwriting grayscale lithography. The ultra-compact chip-spectrometer can work in a very wide range from 900 to 1700 nm wi...

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Visible and near-infrared reflectance spectroscopy—An alternative for monitoring soil contamination by heavy metals

Cited by 281 publications

References 90 publications

Digital Mapping of Toxic Metals in Qatari Soils Using Remote Sensing and Ancillary Data

Digital Mapping of Toxic Metals in Qatari Soils Using Remote Sensing and Ancillary Data

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

Short‐Wave Infrared Chip‐Spectrometer by Using Laser Direct‐Writing Grayscale Lithography

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