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Assessing Statistically Significant Heavy-Metal Concentrations in Abandoned Mine Areas via Hot Spot Analysis of Portable XRF Data
To develop appropriate measures to prevent soil contamination in abandoned mining areas, an understanding of the spatial variation of the potentially toxic trace elements (PTEs) in the soil is necessary. For the purpose of effective soil sampling, this study uses hot spot analysis, which calculates...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5486340/ https://www.ncbi.nlm.nih.gov/pubmed/28629168 http://dx.doi.org/10.3390/ijerph14060654 |
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author | Kim, Sung-Min Choi, Yosoon |
author_facet | Kim, Sung-Min Choi, Yosoon |
author_sort | Kim, Sung-Min |
collection | PubMed |
description | To develop appropriate measures to prevent soil contamination in abandoned mining areas, an understanding of the spatial variation of the potentially toxic trace elements (PTEs) in the soil is necessary. For the purpose of effective soil sampling, this study uses hot spot analysis, which calculates a z-score based on the Getis-Ord Gi* statistic to identify a statistically significant hot spot sample. To constitute a statistically significant hot spot, a feature with a high value should also be surrounded by other features with high values. Using relatively cost- and time-effective portable X-ray fluorescence (PXRF) analysis, sufficient input data are acquired from the Busan abandoned mine and used for hot spot analysis. To calibrate the PXRF data, which have a relatively low accuracy, the PXRF analysis data are transformed using the inductively coupled plasma atomic emission spectrometry (ICP-AES) data. The transformed PXRF data of the Busan abandoned mine are classified into four groups according to their normalized content and z-scores: high content with a high z-score (HH), high content with a low z-score (HL), low content with a high z-score (LH), and low content with a low z-score (LL). The HL and LH cases may be due to measurement errors. Additional or complementary surveys are required for the areas surrounding these suspect samples or for significant hot spot areas. The soil sampling is conducted according to a four-phase procedure in which the hot spot analysis and proposed group classification method are employed to support the development of a sampling plan for the following phase. Overall, 30, 50, 80, and 100 samples are investigated and analyzed in phases 1–4, respectively. The method implemented in this case study may be utilized in the field for the assessment of statistically significant soil contamination and the identification of areas for which an additional survey is required. |
format | Online Article Text |
id | pubmed-5486340 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-54863402017-06-30 Assessing Statistically Significant Heavy-Metal Concentrations in Abandoned Mine Areas via Hot Spot Analysis of Portable XRF Data Kim, Sung-Min Choi, Yosoon Int J Environ Res Public Health Article To develop appropriate measures to prevent soil contamination in abandoned mining areas, an understanding of the spatial variation of the potentially toxic trace elements (PTEs) in the soil is necessary. For the purpose of effective soil sampling, this study uses hot spot analysis, which calculates a z-score based on the Getis-Ord Gi* statistic to identify a statistically significant hot spot sample. To constitute a statistically significant hot spot, a feature with a high value should also be surrounded by other features with high values. Using relatively cost- and time-effective portable X-ray fluorescence (PXRF) analysis, sufficient input data are acquired from the Busan abandoned mine and used for hot spot analysis. To calibrate the PXRF data, which have a relatively low accuracy, the PXRF analysis data are transformed using the inductively coupled plasma atomic emission spectrometry (ICP-AES) data. The transformed PXRF data of the Busan abandoned mine are classified into four groups according to their normalized content and z-scores: high content with a high z-score (HH), high content with a low z-score (HL), low content with a high z-score (LH), and low content with a low z-score (LL). The HL and LH cases may be due to measurement errors. Additional or complementary surveys are required for the areas surrounding these suspect samples or for significant hot spot areas. The soil sampling is conducted according to a four-phase procedure in which the hot spot analysis and proposed group classification method are employed to support the development of a sampling plan for the following phase. Overall, 30, 50, 80, and 100 samples are investigated and analyzed in phases 1–4, respectively. The method implemented in this case study may be utilized in the field for the assessment of statistically significant soil contamination and the identification of areas for which an additional survey is required. MDPI 2017-06-18 2017-06 /pmc/articles/PMC5486340/ /pubmed/28629168 http://dx.doi.org/10.3390/ijerph14060654 Text en © 2017 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Kim, Sung-Min Choi, Yosoon Assessing Statistically Significant Heavy-Metal Concentrations in Abandoned Mine Areas via Hot Spot Analysis of Portable XRF Data |
title | Assessing Statistically Significant Heavy-Metal Concentrations in Abandoned Mine Areas via Hot Spot Analysis of Portable XRF Data |
title_full | Assessing Statistically Significant Heavy-Metal Concentrations in Abandoned Mine Areas via Hot Spot Analysis of Portable XRF Data |
title_fullStr | Assessing Statistically Significant Heavy-Metal Concentrations in Abandoned Mine Areas via Hot Spot Analysis of Portable XRF Data |
title_full_unstemmed | Assessing Statistically Significant Heavy-Metal Concentrations in Abandoned Mine Areas via Hot Spot Analysis of Portable XRF Data |
title_short | Assessing Statistically Significant Heavy-Metal Concentrations in Abandoned Mine Areas via Hot Spot Analysis of Portable XRF Data |
title_sort | assessing statistically significant heavy-metal concentrations in abandoned mine areas via hot spot analysis of portable xrf data |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5486340/ https://www.ncbi.nlm.nih.gov/pubmed/28629168 http://dx.doi.org/10.3390/ijerph14060654 |
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