An Evaluation of Rare Earth M2+ Interference Correction Approaches for Inclusion in the Update of EPA Method 200.8

Collaborative Efforts to Improve Environmental Monitoring
Oral Presentation

Prepared by J. Creed1, S. Smith2, N. Hanks3, R. Wilson4, R. Martin1, P. Creed1, K. Kovalcik1
1 - US EPA, 26 W. Martin Luther King Drive, Cincinnati, Ohio, 45268, United States
2 - University of Cincinnati/U.S. Environmental Protection Agency Research Trainee, 26 W. Martin Luther King Drive, Cincinnati, Ohio, 45268, United States
3 - Student Service Contractor, US EPA, 26 W. Martin Luther King Drive, Cincinnati, Ohio, 45268, United States
4 - Food and Drug Administration, , Cincinnati, Ohio, United States


Contact Information: creed.jack@epa.gov; 513-569-7833


ABSTRACT

ICP-MS based methodologies have benefited from the increased specificity produced by collision cell technologies, but this polyatomic reduction has been achieved at the cost of enhancing doubly charged ion (M2+) based interferences. In this context, the collision cell compromises the overall specificity because rare earth elements can produce M2+ ions (150Nd2+, 150Sm2+, 156Gd2+, and 156Dy2+), which produce false positives on 75As and 78Se when ICP-MS methodologies are utilized for compliance monitoring. Therefore, an update of U.S. Environmental Protection Agency (EPA) Method 200.8 that includes the benefits of polyatomic reduction would ideally address the enhanced M2+ based interferences associated with collision with a goal of improving the overall specificity of the updated method.

In this presentation, various M2+ correction approaches are evaluated with the overall goal of finding M2+ correction approaches that perform well in a variety of sample matrices, over multiple analysis days, using different instrument tunes. In this evaluation, Principle Component Analysis (PCA) is used to evaluate which ions drift together across sample matrix, analysis day and instrument tune to identify possible internal standards that could be used to track the M2+ drift across matrix within an analysis batch. Based on PCA clusters, various internal standards will be selected and evaluated in a format that compares sample specific across-day performance to results obtained using ICP-QQQ-MS and HR-ICP-MS. This should help identify approaches that have a bias relative to the true value estimated by these two techniques. Also, a hierarchical model is used to estimate a quantitative distribution for the various internal standards treatments using the ICP-QQQ-MS and HR-ICP-MS results as a zero point for these distributions. Finally, the bias and width of the associated distribution for various internal standard treatments will be discussed in the context of updating the M2+ correction approaches within revised EPA Method 200.8.