Development and Application of Portable XRF Technology for Estimation of Mining Waste Acid-Generating Potential

Acid-base accounting (ABA) is a batch laboratory test commonly used in the prediction of acid production from mine wastes.  Although proven useful for directing material management practice, analysis is expensive and time-consuming.  At the Copper Basin Mining District Site in southeastern Tennessee, remedial actions are being conducted in iterative phases.  The progressive cleanup plan calls for the segregation of materials with ‘high’ and ‘low’ acid-generating potential so that they can be handled and disposed by different means.  This requires rapid field decisions that are not adequately supported by the standard laboratory analytical methods. 

Although visual waste identification was possible in some instances, an alternative field-based method for estimating acid-generating potential was sought that would further assist ‘real-time’ decisions.  The primary objectives were to provide the construction manager with an effective tool to select appropriate disposal options while minimizing contractor downtime and meeting aggressive timelines.  Portable x-ray fluorescence technology (XRF) was identified as a potential solution based on emerging capabilities in sulfur quantification.  The correlation between sulfur concentration and acid-generating potential was established for a range of waste materials present on site based on laboratory analysis.  XRF sulfur test results were then used along with laboratory sulfur data to establish an empirical relationship used to calibrate the instrument.  Regression analysis was performed to develop an equation to estimate acid-generating potential from the XRF sulfur results within certain decision bounds. 

Qualified field personnel have used the XRF technology to direct Phase 1 of the remedial action which has required the handling of over 500,000 cubic yards of diverse but generally ‘bad actor’ waste materials.   Field XRF results and correlated lab ABA data collected during Phase 1 will be used to refine the empirical calibration and regression analyses to provide a more precise decision-making tool for subsequent remedial phases.

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