| Literature DB >> 31036842 |
Jyh-Jaan Steven Huang1,2,3, Sheng-Chi Lin4, Ludvig Löwemark5,6, Sofia Ya Hsuan Liou7,8, Queenie Chang7,9, Tsun-Kuo Chang10, Kuo-Yen Wei7,8, Ian W Croudace11.
Abstract
Conventional pollution monitoring strategies for heavy metals are often costly and unpractical. Innovative sampling and analytical approaches are therefore needed to efficiently monitor large areas. This study presents a novel, simple, fast, and inexpensive method to monitor heavy metal pollution that uses cation-exchange resin sachets and the micro-XRF core-scanning technique (XRF-CS). The resin passive samplers act as concentrators of cationic species and can be readily deployed spatially and temporally to record pollution signals. The large number of analytical tasks are then overcome by the fast and non-destructive XRF-CS to precisely assess elemental concentrations. Quantifying element loading involves direct comparison with a set of identically prepared and scanned resin reference standards containing Ca, Ti, Cr, Mn, Ni, Cu, Zn, Pb. The results show that within the test range (from 0-1000 s mg kg-1), the calibration lines have excellent regressions (R2 ≥ 0.97), even at the shortest exposure time (1 s). A pilot field survey of a suspected polluted area in central Taiwan, where 30 resin sachets had been deployed, identified a pollution hot spot in a rapid and economical manner. Therefore, this approach has the potential to become a valuable tool in environmental monitoring and forensics.Entities:
Year: 2019 PMID: 31036842 PMCID: PMC6488570 DOI: 10.1038/s41598-019-43015-x
Source DB: PubMed Journal: Sci Rep ISSN: 2045-2322 Impact factor: 4.379
Figure 1Scatter plots showing linear regression lines and correlation coefficients between concentrations and XRF-CS counts (100 s exposure time, with the standard deviation of each measurement) of resin reference standards for elements generally used in pollution studies (Cr, Mn, Ni, Cu, Zn, Pb).
Figure 2Combined results of concentrations vs. XRF-CS counts for five tested exposure times. Correlation coefficients of all experiments are ≥0.97, suggesting the chosen exposure times have only a limited influence on the accuracy of XRF-CS results.
Figure 3A pilot field survey with 30 resin samples in a suspected polluted farm area in central Taiwan. The height of the bars represents variations for pollution-related elements (Cr, Mn, Ni, Cu, Zn, Pb) in XRF-CS counts across the monitoring area. Each black cell represents an area of 0.5 × 0.5 km; the pollution hot spot is identified in the upper left of the grid. The satellite image was taken on 19th November 2012 from DigitalGlobe with a Google Earth platform and further modified by Arc GIS 10.2.