The traditional method for sampling for lead on surfaces uses inductively coupled plasma atomic emission spectroscopy (ICP-AES) to analyze the concentration of lead and other metals on surfaces. This type of analysis is time consuming and costly. Field portable X-ray fluorescence (FP XRF) is another analysis method that is not as accurate as traditional laboratory methods but is more cost efficient and has a turnaround time of less than an hour. The primary goal of this study is to find the best method to increase the level of agreement between the ICP-AES concentrations and the FP XRF concentrations when analyzing lead concentrations on surface wipes. Inverse regression and ratio of the means correction factors were analyzed to try to improve the prediction of ICP-AES concentrations using FP XRF results. Fifty-seven dust wipe samples were analyzed using a split-half design. Half of the samples were used to create the correction factor and the other half were used to test the level of agreement. Linear regression and Bland -Altman plots were used to determine the correction factor that provided the highest level of agreement. A ratio of the means correction factor was determined to be the most appropriate.
Keywords: Superfund; correction factor; dust wipes; lead; level of agreement.