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Rapid assessment of heavy metal pollution using ion-exchange resin sachets and micro-XRF core-scanning
- Source :
- Scientific Reports, Scientific Reports, Vol 9, Iss 1, Pp 1-6 (2019)
- Publication Year :
- 2019
- Publisher :
- Nature Publishing Group UK, 2019.
-
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 (R 2 ≥ 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.
- Subjects :
- 0301 basic medicine
Pollution
media_common.quotation_subject
lcsh:Medicine
Core (manufacturing)
Article
03 medical and health sciences
0302 clinical medicine
Environmental monitoring
Calibration
Ion-exchange resin
Process engineering
lcsh:Science
media_common
Multidisciplinary
business.industry
lcsh:R
Sampling (statistics)
Metal pollution
Rapid assessment
030104 developmental biology
Sustainability
Environmental science
lcsh:Q
business
030217 neurology & neurosurgery
Subjects
Details
- Language :
- English
- ISSN :
- 20452322
- Volume :
- 9
- Database :
- OpenAIRE
- Journal :
- Scientific Reports
- Accession number :
- edsair.doi.dedup.....384fc81791a73c140686de6a308ac242