Abstract

The use of portable X-ray fluorescence (PXRF) and inductively coupled plasma atomic emission spectrometry (ICP-AES) increases the rapidity and accuracy of soil contamination mapping, respectively. In practice, it is often necessary to repeat the soil contamination assessment and mapping procedure several times during soil management within a limited budget. In this study, we have developed a rapid, inexpensive, and accurate soil contamination mapping method using a PXRF data and geostatistical spatial interpolation. To obtain a large quantity of high quality data for interpolation, in situ PXRF data analyzed at 40 points were transformed to converted PXRF data using the correlation between PXRF and ICP-AES data. The method was applied to an abandoned mine site in Korea to generate a soil contamination map for copper and was validated for investigation speed and prediction accuracy. As a result, regions that required soil remediation were identified. Our method significantly shortened the time required for mapping compared to the conventional mapping method and provided copper concentration estimates with high accuracy similar to those measured by ICP-AES. Therefore, our method is an effective way of mapping soil contamination if we consistently construct a database based on the correlation between PXRF and ICP-AES data.

Highlights

  • Mine tailings generally contain several types of potentially toxic elements (PTEs) and can widely be dispersed by percolating rainwater or mechanical transport in runoff

  • To address and overcome these limitations, this study aims to develop a rapid and accurate soil contamination mapping method using in situ portable X-ray fluorescence (PXRF) analysis data corrected by inductively coupled plasma atomic emission spectrometry (ICP-AES) data and geographic information systems (GIS)

  • We considered Kriging, a common interpolation method used in geostatistics, to predict copper concentrations in soil over the entire grid in this study

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Summary

Introduction

Mine tailings generally contain several types of potentially toxic elements (PTEs) and can widely be dispersed by percolating rainwater or mechanical transport in runoff. ICP-AES has a few disadvantages, such as non-portability, high operating costs, and lengthy period required for elemental analysis due to complex preprocessing (e.g., an acid digestion of the sample is needed when analyzing soil samples) [9,10,11,12]. These time and cost constraints can reduce the amount of accessible data that affects the quality of the soil contamination mapping

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