Abstract

Understanding spatial variation of potentially toxic trace elements (PTEs) in soil is necessary to identify the proper measures for preventing soil contamination at both operating and abandoned mining areas. Many studies have been conducted worldwide to explore the spatial variation of PTEs and to create soil contamination maps using geostatistical methods. However, they generally depend only on inductively coupled plasma atomic emission spectrometry (ICP–AES) analysis data, therefore such studies are limited by insufficient input data owing to the disadvantages of ICP–AES analysis such as its costly operation and lengthy period required for analysis. To overcome this limitation, this study used both ICP–AES and portable X-ray fluorescence (PXRF) analysis data, with relatively low accuracy, for mapping copper and lead concentrations at a section of the Busan abandoned mine in Korea and compared the prediction performances of four different approaches: the application of ordinary kriging to ICP–AES analysis data, PXRF analysis data, both ICP–AES and transformed PXRF analysis data by considering the correlation between the ICP–AES and PXRF analysis data, and co-kriging to both the ICP–AES (primary variable) and PXRF analysis data (secondary variable). Their results were compared using an independent validation data set. The results obtained in this case study showed that the application of ordinary kriging to both ICP–AES and transformed PXRF analysis data is the most accurate approach when considers the spatial distribution of copper and lead contaminants in the soil and the estimation errors at 11 sampling points for validation. Therefore, when generating soil contamination maps for an abandoned mine, it is beneficial to use the proposed approach that incorporates the advantageous aspects of both ICP–AES and PXRF analysis data.

Highlights

  • Mining is a global industry that can be hazardous to public health and safety, and can cause damage to the surrounding environment, including land, soil, water, and forests [1]

  • Through a comparative analysis that considered the spatial variations of copper and in the soil and the estimation errors at the points of 11 validation samples, the proposed approach 3, lead concentrations in the soil and the estimation errors at the points of 11 validation samples, the which applies ordinary kriging to both inductively coupled plasma atomic emission spectrometry (ICP–AES) and transformed portable X-ray fluorescence (PXRF) analysis data by considering proposed approach 3, which applies ordinary kriging to both ICP–AES and transformed PXRF

  • The correlation between the ICP–AES and PXRF analysis data, was determined to be the most accurate analysis data by considering the correlation between the ICP–AES and PXRF analysis data, was method in generating soil contamination maps because it can incorporate the advantageous aspects of both data types

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Summary

Introduction

Mining is a global industry that can be hazardous to public health and safety, and can cause damage to the surrounding environment, including land, soil, water, and forests [1]. Among the various environmental impacts of mining, contamination of soil is significant because mine waste produced by metal-mining activities generally contains higher content of potentially toxic trace elements (PTEs) than that in regular industrial waste. These substances can become widely dispersed throughout mining areas unless proper measures for isolation or treatment are taken [2,3]. Res. Public Health 2016, 13, 384; doi:10.3390/ijerph13040384 www.mdpi.com/journal/ijerph

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