Correlation of X-ray Fluorescence Spectrometry And Inductively Coupled Plasma Atomic Emission Spectroscopy for Elemental Determination In Composted Products

Weindorf, David C.; Sarkar, Reshmi; Dia, Mahendra; Wang, H.; Chang, Qing; Haggard, Beatrix; McWhirt, Amanda; Wooten, A. Lake

doi:10.1080/1065657x.2008.10702361

Cited by 36 publications

(25 citation statements)

References 5 publications

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“…The major concern of PXRF performance is the non-homogeneity of efficiency for different elements (Kalnicky and Singhvi, 2001;Migliori et al, 2011;Weindorf et al, 2011), which is still being improved upon by users and manufacturers. Nevertheless, PXRF is able to offer acceptable quantitative results regarding chemical composition of the studied materials, as reported by VanCott et al (1999) and Weindorf et al (2008).…”

Section: Introductionmentioning

confidence: 62%

Characterizing soils using a portable X-ray fluorescence spectrometer: 1. Soil texture

2011

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Section: Introductionmentioning

confidence: 62%

Characterizing soils using a portable X-ray fluorescence spectrometer: 1. Soil texture

2011

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“…For example, Weindorf et al (2008) tested the performance of PXRF compared to ICP for determining the elemental composition of compost products. They scanned samples in dried, ground condition, pressed into a sample cup.…”

Section: Pxrf For Measuring Soil Contaminantsmentioning

confidence: 99%

Potential of integrated field spectroscopy and spatial analysis for enhanced assessment of soil contamination: A prospective review

et al. 2015

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a b s t r a c tThere are tens of millions of contaminated soil sites in the world, and with an increasing population and associated risk there is a growing pressure to remediate them. A barrier to remediation is the lack of cost-effective approaches to assessment. Soil contaminants include a wide range of natural and synthetic metallic and organic compounds and minerals thus making analytical costs potentially very large. Further, soil contaminants show a large degree of spatial variation which increases the burden on sampling costs. This paper reviews potentially cost-effective methods for measurement, sampling design, and assessment. Current tiered investigation approaches and sampling strategies can be improved by using new technologies such as proximal sensing. Design of sampling can be aided by on-the-go proximal soil sensing; and expedited by subsequent adaptive spatially optimal sampling and prediction procedures enabled by field spectroscopic methods and advanced geostatistics. Field deployment of portable Visible & Near Infrared [wavelength 400-2500 nm] (Vis-NIR) and X-ray fluorescence (PXRF) spectroscopies will require special calibration approaches but show huge potential for synergistic use. The use of mid-infrared spectroscopy [wavelength 2500-25,000 nm, wavenumber 4000-400 cm −1 ] (MIR) for field implementation requires further adaptive research. We propose an integrated field-deployable methodology as a basis for further developments. Crown

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“…Such sensors have the advantage of being a portable proximal sensing tool that provides immediate estimates of contents of various chemical elements in soils, with none or minimum sample pre-processing [32,33]. Results showed that pXRF devices provide adequate analytical accuracy when compared to conventional laboratory-based methods [17,32,34,35]. On the other hand, few efforts have been made to apply proximal sensors on predictions of soil physical properties [33].…”

Section: Study Area and Laboratory Analysesmentioning

confidence: 99%

Proximal Sensing and Digital Terrain Models Applied to Digital Soil Mapping and Modeling of Brazilian Latosols (Oxisols)

et al. 2016

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Digital terrain models (DTM) have been used in soil mapping worldwide. When using such models, improved predictions are often attained with the input of extra variables provided by the use of proximal sensors, such as magnetometers and portable X-ray fluorescence scanners (pXRF). This work aimed to evaluate the efficiency of such tools for mapping soil classes and properties in tropical conditions. Soils were classified and sampled at 39 locations in a regular-grid design with a 200-m distance between samples. A pXRF and a magnetometer were used in all samples, and DTM values were obtained for every sampling site. Through visual analysis, boxplots were used to identify the best variables for distinguishing soil classes, which were further mapped using fuzzy logic. The map was then validated in the field. An ordinary least square regression model was used to predict sand and clay contents using DTM, pXRF and the magnetometer as predicting variables. Variables obtained with pXRF showed a greater ability for predicting soil classes (overall accuracy of 78% and 0.67 kappa index), as well as for estimating sand and clay contents than those acquired with DTM and the magnetometer. This study showed that pXRF offers additional variables that are key for mapping soils and predicting soil properties at a detailed scale. This would not be possible using only DTM or magnetic susceptibility.

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Correlation of X-ray Fluorescence Spectrometry And Inductively Coupled Plasma Atomic Emission Spectroscopy for Elemental Determination In Composted Products

Cited by 36 publications

References 5 publications

Characterizing soils using a portable X-ray fluorescence spectrometer: 1. Soil texture

Characterizing soils using a portable X-ray fluorescence spectrometer: 1. Soil texture

Potential of integrated field spectroscopy and spatial analysis for enhanced assessment of soil contamination: A prospective review

Proximal Sensing and Digital Terrain Models Applied to Digital Soil Mapping and Modeling of Brazilian Latosols (Oxisols)

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