X-ray fluorescence (XRF) in the investigation of the composition of earth materials: a review and an overview

Oyedotun, Temitope D. Timothy

doi:10.1080/24749508.2018.1452459

Cited by 85 publications

(41 citation statements)

References 37 publications

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“…In addition, the interference in the line of X-ray radiation can be corrected, thereby enabling high accuracy and precision to be easily attained. Another advantage of XRF is the sample preparation, which is simple, time saving and non-destructive [Oyedotun, 2018]. The hXRF measuring device functional principle is as follows: Figure 4 shows the used hXRF measuring device and the obtained results.…”

Section: X-ray Fluorescence Analysis For Heavy Metal Detectionmentioning

confidence: 99%

Investigation of Heavy Metal Sources on Railways: Ballast Layer and Herbicides

Samarska¹,

Kovrov²,

Zelenko³

2020

J. Ecol. Eng.

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Railway operation can result in the significant environment contamination with heavy metals. The aim of the study was to broaden the knowledge about the railway transport as a source of heavy metals. Railway ballast stones and herbicides were chosen as the objects of the research since these contamination sources on railways are hardly investigated. The location of sampling the ballast stones was a passenger station, which is characterized by the high traffic intensity. The three most common glyphosate-based herbicides and two combination system herbicides of burn-down with other active agents were chosen for the analysis. The heavy metal content in the railway ballast stones was detected by means of XRF, in the herbicides-by means of MP-AES. The railway ballast stones did not contain a sufficient amount of Cd, Co, Mo, Pd, Sn and W for detection. Pb and As were detected at the low concentration of less than 35 ppm only in several samples. The research results showed that the investigated railway ballast contained a significant amount of Fe, Mn, Cu, Cr and Ni. According to the absolute content of HMs in the contaminated ballast layer, they can be arranged in the following sequence: Fe > Mn > Cu > Cr > Ni > Zn > Pb > As. The content of Fe in the contaminated ballast stones was strongly correlated with that of Ni (r = 0.972), Cr (r = 0.954) and Mn (r = 0.943). These metals are components of the railway steel. Therefore, their source can be the abrasion of rails and wheels. All the investigated herbicides contained Cd, Co, Cr, Cu, Fe, Mn, Ni, Pb and Zn. The highest content of Cd, Cr, Ni and Pb was detected in the "Anti field bindweed" herbicide, which can be related to its complicated composition. Compared to the heavy metal content in the ballast stones, the herbicides can be considered a negligible source of these pollutants.

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Section: X-ray Fluorescence Analysis For Heavy Metal Detectionmentioning

confidence: 99%

Investigation of Heavy Metal Sources on Railways: Ballast Layer and Herbicides

Samarska¹,

Kovrov²,

Zelenko³

2020

J. Ecol. Eng.

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“…The ED-XRF analysis gives the chemical composition as major oxides and trace elements, which helps to identify the presence of heavy minerals, mainly the monazite mineral in soil samples. The ED-XRF technique provides a rapid multi-elemental analysis of geological samples, especially the major, trace, radioactive, and rare earth elements in soil and beach sediments [77,78]. These results paved the qualitative confirmation of minerals present in the soil [79].…”

Section: Bulk Geochemistry Of Soil Samplesmentioning

confidence: 84%

Monazite chemistry and its distribution along the coast of Neendakara–Kayamkulam belt, Kerala, India

et al. 2020

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The beach sands along the coasts of India contain large reserves of strategic minerals like ilmenite, monazite, zircon, etc. Monazite mineral is primarily used as an ore for extracting rare earths particularly cerium and lanthanum. In the present study, the chemistry and distribution of monazite found in the beach sands of Neendakara-Kayamkulam belt in Kerala, south India, is studied using advanced techniques and standardized methods. Beach sediments were collected and analyzed for the texture, and mineralogy reveals that the study area contains characteristically fine sand with maximum 98.9% total heavy minerals (THM) content with ilmenite as predominant mineral species. The content of monazite ranges from 0.1 to 1.4%. A combination of unit operations like gravity separation, magnetic separation and electrostatic separation techniques were applied to the beach sand to recover monazite mineral. The data indicate that samples show a maximum yield of about 81% for THM and 0.5% for monazite. The ED-XRF, XRD and SEM-EDS analysis gives reliable results on the chemistry of monazite. The major chemical constituents of monazite mineral like Ce 2 O 3 , La 2 O 3 , P 2 O 5 corresponds to 26.658, 13.421 and 23.649%, respectively. The SEM reveals the weathering mechanism, both mechanical and chemical, occurred in monazite mineral. Advanced characterization of monazite mineral will influence positively the efficiency of determining their potential applications.

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“…In order to verify the robustness of the proposed method, the method is further tested by using the agricultural water Scene 2 with different background [24][25][26]. The results of the four methods are as shown in Fig.…”

Section: Results Of Insar Image Preprocessingmentioning

confidence: 99%

Monitoring and scheduling of pollution disaster in agricultural waters based on INSAR

Liu¹,

Zhang²,

Li³

et al. 2019

Desalination and Water Treatment

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Objective: To improve the quality of monitoring image in agricultural waters by effective methods, to obtain information of the pollution disaster in agricultural waters in time, to provide the necessary data for the disaster management and decision making of agricultural waters, and to promote the development of agricultural economy in this region. Methods: by using the monitoring and scheduling method for pollution disaster in agricultural waters based on INSAR, comprehensive and accurate monitoring of pollution disaster in agricultural waters can be conducted. SRTM3 DEM is used to eliminate baseline error in INSAR interferogram. According to different scattering characteristics of different ground objects in the INSAR image, the gray value is different, and a two-dimensional gray histogram is built to preprocess the INSAR image so as to avoid the false alarm in the detection of the edge of the agricultural waters. Through the monitoring method of ground wave spectrum, the two directions reflection ratio factor of waterbody is measured, and the correlation between the pollution of agricultural waters and the ground spectrum is studied, and the monitoring and scheduling of the pollution disaster in the agricultural waters are effectively carried out. Results: there is a significant correlation between the pollution in agricultural waters and the satellite reflectance spectrum on the ground, with a correlation coefficient of about 0.8. The false area which is not connected with the agricultural waters of the preprocessed INSAR image is almost completely removed by using the proposed method. The boundary of the extracted water area is well matched with the boundary of the actual image. The false alarm rate and the leakage rate for processing the agricultural waters image under different scenes are all very low, and the accuracy of the INSAR image extraction and calculation efficiency are better and with good robustness. The proposed method can reduce the strong scattering point and the speckle noise of the building, and effectively restrain the edge of the buildings, such as the buildings around the agricultural waters. The information of disaster change in agricultural waters obtained by the proposed method is relatively accurate. Conclusion: the proposed method can extract the image of agricultural waters and obtain the information of the pollution disaster in agricultural waters in real time and accurately, so as to realize the effective monitoring and scheduling of the pollution disaster in the agricultural waters.

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X-ray fluorescence (XRF) in the investigation of the composition of earth materials: a review and an overview

Cited by 85 publications

References 37 publications

Investigation of Heavy Metal Sources on Railways: Ballast Layer and Herbicides

Investigation of Heavy Metal Sources on Railways: Ballast Layer and Herbicides

Monazite chemistry and its distribution along the coast of Neendakara–Kayamkulam belt, Kerala, India

Monitoring and scheduling of pollution disaster in agricultural waters based on INSAR

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