You are here:
RESIDENTIAL SOIL SAMPLING PLAN: COMPARISON OF LABORATORY AND FIELD X-RAY FLUORESCENCE (XRF) ANALYSIS AND SAMPLE PREPARATION.
Impact/Purpose:
The Field Sampling Plan Objectives included: Support of residential soil removals and remediation; Collect data to compare the accuracy and precision of XRF with traditional EPA Contract Laboratory Program (CLP) analysis; Quantify the effects of soil preparation (drying and sieving) to correlate Field XRF results to dried and sieved samples submitted to a Laboratory for analysis.
Description:
In the past, Region 10 has relied exclusively on fixed-site laboratory analyses of soil samples for Remedial Investigation/Feasibility Studies and Risk Assessments. The objectives of this sampling effort included soil analyses for removal and remedial actions as well as collecting data to correlate field XRF analyses of lead, arsenic, and zinc with prepared samples submitted to a laboratory (e.g. use field analysis as a surrogate for laboratory analysis of prepared samples). Surprisingly, correlation coefficients between various levels of sample preparation analyzed by XRF and a fixed site laboratory were not dependent upon soil moisture or sieving. The correlation coefficients were independent of soil moisture or sieving, but the slopes of the regressions varied with sample preparation. For the primary contaminant, lead, the correlation coefficients (r2) were: .94; .92 and .92 for sieved and dried; dried; and un-prepared (un-sieved at field moisture) samples, respectively. For arsenic, the correlation coefficients were: .97; .96 and .86, respectively. For zinc, the correlation coefficients wer: .94; .86 and .94, respectively. Future sampling soil efforts will rely on un-prepared XRF analyses with confirmatory laboratory analyses of prepped samples when XRF results are close to action levels. Benefits of XRF and reduced sample preparation include financial, temporal, and logistical savings. Future plans include re-examining sampling and analysis protocols to balance sampling efforts with decision errors and to apply real time data acquisition to adaptive sampling techniques.