Better assessment of the distribution of As and Pb in soils in a former smelting area, using ordinary co-kriging and sequential Gaussian co-simulation of portable X-ray fluorescence (PXRF) and ICP-AES data

Kim, Ho Rim; Kim, Kyoung-Ho; Yu, Soonyoung; Moniruzzaman, Md.; Hwang, Sang Il; Lee, Goon Taek; Yun, Seong Taek

doi:10.1016/j.geoderma.2019.01.031

Cited by 29 publications

(14 citation statements)

References 51 publications

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“…The high values of Pb (Figure 3c,d) and Cd (Figure 3e,f) were mainly located in the southeast and northwest parts of the study area, while the high values of As (Figure 3g,h) were found in the north and south portions. The spatial patterns of heavy metals pollution produced by OK and COK were very similar, but COK captured more local variations, further confirming the advantage of COK over OK and that use of covariates in COK could provide more detailed information [28,49]. These results confirmed the conclusions of a previous study [22] that the application of XRF measurements as covariates could improve the spatial interpolation of soil heavy metals.…”

Section: Resultssupporting

confidence: 81%

“…However, few studies of the use of PXRF data as covariates during mapping of soil heavy metals have been conducted to date. Kim et al [28] used PXRF measurement as covariates during analysis of the spatial distribution of As and Pb in soils in a former smelting area in South Korea and found that PXRF could reduce the effort required for collection of soil samples for conventional analysis and improve spatial estimations of polluted areas. However, to the best of our knowledge, few studies have used data from PXRF measurements as covariates to estimate spatial distributions of Cr, Pb, Cd, As and Ni in soil with COK to date [23,26,27,28].…”

Section: Introductionmentioning

confidence: 99%

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Improvement of Spatial Modeling of Cr, Pb, Cd, As and Ni in Soil Based on Portable X-ray Fluorescence (PXRF) and Geostatistics: A Case Study in East China

Xia

Shao

et al. 2019

IJERPH

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To verify the feasibility of portable X-ray ﬂuorescence (PXRF) for rapidly analyzing, assessing and improving soil heavy metals mapping, 351 samples were collected from Fuyang District, Hangzhou City, in eastern China. Ordinary kriging (OK) and co-ordinary kriging (COK) combined with PXRF measurements were used to explore spatial patterns of heavy metals content in the soil. The Getis-Ord index was calculated to discern hot spots of heavy metals. Finally, multi-variable indicator kriging was conducted to obtain a map of multi-heavy metals pollution. The results indicated Cd is the primary pollution element in Fuyang, followed by As and Pb. Application of PXRF measurements as covariates in COK improved model accuracy, especially for Pb and Cd. Heavy metals pollution hot spots were mainly detected in northern Fuyang and plains along the Fuchun River in southern Fuyang because of mining, industrial and traffic activities, and irrigation with polluted water. Area with high risk of multi-heavy metals pollution mainly distributed in plain along the Fuchun River and the eastern Fuyang. These findings certified the feasibility of using PXRF as an efficient and reliable method for soil heavy metals pollution assessment and mapping, which could contribute to reduce the cost of surveys and pollution remediation.

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Section: Resultssupporting

confidence: 81%

Section: Introductionmentioning

confidence: 99%

Improvement of Spatial Modeling of Cr, Pb, Cd, As and Ni in Soil Based on Portable X-ray Fluorescence (PXRF) and Geostatistics: A Case Study in East China

Xia

Shao

et al. 2019

IJERPH

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“…These techniques are also less used in scientific works, which in addition to the techniques previously discussed, use techniques that involve fluorescence, microwave induced plasma, electron capture detector and X-ray in diverse matrices. In soil samples, Pierangeli et al (2015) used TXRF and obtained 33.3 μg L -1 , Zhong et al (2019) with gas chromatograph with an electron capture detector (GC ECD) found 480 µg kg -1 and Kim et al (2019) with PXRF reported 1,670 µg kg -1 . Analyzing samples in fish, Gallego Ríos et al (2018) obtained 76.7 µg kg -1 using MIP OES and in samples of Eisenia fetida, Wang et al (2016) obtained 200 µg kg -1 with HG AFS.…”

Section: Resultsmentioning

confidence: 99%

“…6, n. 14, p. 803-817. Oliveira et al, 2016;Souza et al, 2016;Pereira et al, 2016), hydride generation combined with inductively coupled plasma optical emission spectrometry HG ICP OES (Kim et al, 2019), hydride generation combined with atomic fluorescence spectrometry (HG AFS) (Wang et al, 2016), microwave induced plasma optical emission spectrometry (MIP OES) (Gallego Ríos et al, 2018), visible ultraviolet spectroscopy (UV VIS) (Gürkan et al, 2015), total reflection X-ray fluorescence (TXRF) (Pierangeli et al, 2015) and portable X-ray fluorescence (PXRF) (García-Rico et al, 2019;Kim et al, 2019).…”

Section: Introductionmentioning

confidence: 99%

Arsenic quantification techniques and ISO/IEC 17025 accreditation in Brazil

Santos¹,

Busato²,

Heringer³

et al. 2019

Rev. Bras. Gest. Amb. Sustent.

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The importance of arsenic (As) quantification in environmental compartments is due to its risks to ecosystems and public health. There are reports of high concentrations of this metalloid in Brazil and technological differences between states are observed. The objective of this work was to present and discuss current scenarios of accreditation and compare the limit of quantification (LOQ) of As by analytical technique in Brazil. Data from accredited laboratories were collected on Inmetro website and in state metrological networks and then grouped and analyzed by state, matrix and analytical technique. There are large discrepancies between the number of laboratories per state and a good correlation with gross domestic product (GDP). Almost all laboratories have a LOQ less than the environmental limits. The observed list of techniques sorted from lowest to highest LOQ values is: for liquid samples ICP MS (inductively coupled plasma mass spectrometry), ET AAS (electrothermal atomic absorption spectrometry), HG AAS (hydride generation combined with atomic absorption spectrometry) or HG ICP OES (hydride generation combined with inductively coupled plasma optical emission spectrometry) and UV VIS (visible ultraviolet spectroscopy); for solids samples HG ICP OES, ICP MS, HG AAS, ET AAS and FAAS (flame atomic absorption spectrometry); and for bioindicators ICP MS, HG ICP OES. Analysis of As species is accredited in only one laboratory, but does not include all species.

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“…These advantages of p-XRF could potentially enhance the spatial prediction of soil PTEs, with some attempts previously reported. For example, in a study conducted in a former smelting area, Kim et al (2019) [56] proved that using p-XRF measurements as an auxiliary for COK improved the estimation of the PTE spatial distribution even with a smaller sample size. In another study, Xia et al (2019) [57] reported that using p-XRF measurements as covariates in COK improved the PTE mapping accuracy in agricultural soils.…”

Section: Introductionmentioning

confidence: 99%

Improved Mapping of Potentially Toxic Elements in Soil via Integration of Multiple Data Sources and Various Geostatistical Methods

Xia

Zhu³

et al. 2020

Remote Sensing

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Soil pollution by potentially toxic elements (PTEs) has become a core issue around the world. Knowledge of the spatial distribution of PTEs in soil is crucial for soil remediation. Portable X-ray fluorescence spectroscopy (p-XRF) provides a cost-saving alternative to the traditional laboratory analysis of soil PTEs. In this study, we collected 293 soil samples from Fuyang County in Southeast China. Subsequently, we used several geostatistical methods, such as inverse distance weighting (IDW), ordinary kriging (OK), and empirical Bayesian kriging (EBK), to estimate the spatial variability of soil PTEs measured by the laboratory and p-XRF methods. The final maps of soil PTEs were outputted by the model averaging method, which combines multiple maps previously created by IDW, OK, and EBK, using both lab and p-XRF data. The study results revealed that the mean PTE content measured by the laboratory methods was as follows: Zn (127.43 mg kg−1) > Cu (31.34 mg kg−1) > Ni (20.79 mg kg−1) > As (10.65 mg kg−1) > Cd (0.33 mg kg−1). p-XRF measurements showed a spatial prediction accuracy of soil PTEs similar to that of laboratory analysis measurements. The spatial prediction accuracy of different PTEs outputted by the model averaging method was as follows: Zn (R2 = 0.71) > Cd (R2 = 0.68) > Ni (R2 = 0.67) > Cu (R2 = 0.62) > As (R2 = 0.50). The prediction accuracy of the model averaging method for five PTEs studied herein was improved compared with that of the laboratory and p-XRF methods, which utilized individual geostatistical methods (e.g., IDW, OK, EBK). Our results proved that p-XRF was a reliable alternative to the traditional laboratory analysis methods for mapping soil PTEs. The model averaging approach improved the prediction accuracy of the soil PTE spatial distribution and reduced the time and cost of monitoring and mapping PTE soil contamination.

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Better assessment of the distribution of As and Pb in soils in a former smelting area, using ordinary co-kriging and sequential Gaussian co-simulation of portable X-ray fluorescence (PXRF) and ICP-AES data

Cited by 29 publications

References 51 publications

Improvement of Spatial Modeling of Cr, Pb, Cd, As and Ni in Soil Based on Portable X-ray Fluorescence (PXRF) and Geostatistics: A Case Study in East China

Improvement of Spatial Modeling of Cr, Pb, Cd, As and Ni in Soil Based on Portable X-ray Fluorescence (PXRF) and Geostatistics: A Case Study in East China

Arsenic quantification techniques and ISO/IEC 17025 accreditation in Brazil

Improved Mapping of Potentially Toxic Elements in Soil via Integration of Multiple Data Sources and Various Geostatistical Methods

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