Application of the U.S. EPA procedure for determining method detection limits to EDXRF measurement of filter-based aerosol samples

ABSTRACT

The U.S. Environmental Protection Agency (EPA) modified its guidance on determining “method detection limits” (MDL) in 2017. The recommended procedures have not yet been applied to the analyses routinely done on filter samples for EPA’s Chemical Speciation Network (CSN). This paper applies the new EPA procedure for estimating MDL to Energy Dispersive X-Ray Fluorescence (EDXRF) analysis of atmospheric aerosol samples collected on filters. The procedure involves estimating MDL by two approaches – statistical distributions of unloaded blank sample measurements and lightly loaded, spiked samples – and sets the MDL as the maximum of these two approaches. Spiked samples at low concentrations were developed using an aerosol deposition chamber to follow this approach. The MDL procedure was initially conducted on one EDXRF instrument, and the spike-based MDL was found to be higher than blank-based MDL for 28 of the 31 elements. The blank-based MDL was higher than the spike-based MDL for Si, K and Fe, which are common contaminants present in filter raw media or arising from EDXRF hardware. The annual verification performed using five EDXRF analyzers demonstrated that the MDL estimated following the EPA procedure was stable over time and analyzers for all elements except K, which yielded a higher MDL.

Implications: Lightly loaded reference materials (RM) were developed for Energy Dispersive X-ray Fluorescence (EDXRF) measurements of elemental concentrations in filter-based particulate matter samples using a novel aerosol generation chamber. These RM were then used to estimate method detection limits (MDL) following U.S. Environmental Protection Agency guidance. These new MDL estimates were compared to alternative estimates and, for most elements, are higher. Our work provides EDXRF users with MDL estimates for each element and an assessment of different MDL estimation approaches.

Acknowledgment

The authors acknowledge funding in cooperation with the U.S. EPA and the Interagency Monitoring of PROtected Visual Environments (IMPROVE) program (National Park Service cooperative agreement P18AC01222).

Data availability statement

The data that support the findings of this study are available from the corresponding author, NPH, upon reasonable request.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This work was supported by the US Environmental Protection Agency and National Park Service [P18AC01222].

Notes on contributors

Nicole Pauly Hyslop

Nicole Pauly Hyslop is the Associate Director for Quality Research in the Air Quality Research Center at the University of California Davis. Dr. Hyslop conducts research to characterize data quality to gain a better understanding of the sources of error in the measurements and improve quality assurance protocols to identify and reduce errors.

Yifan Liu

Yifan Liu has been a post-doc in the Air Quality Research Center at the University of California Davis since 2019. Dr. Liu’s research focuses on gravimetric data analysis and reference material development. Dr. Liu received his PhD in Chemical and Biological Engineering from Johns Hopkins University where he specialized on nanomaterials.

Sinan Yatkin

Sinan Yatkin was an Assistant Project Scientist for the Air Quality Research Center at the University of California Davis when this work was performed. He was involved in the research of XRF method development and generation of reference materials.

Krystyna Trzepla

Krystyna Trzepla was the Laboratory Manager for the Air Quality Research Center at the University of California Davis until her retirement in 2020. Ms. Trzepla provided support for all research studies involving monitoring particles in the atmosphere, with special emphasis on the application of elastic lidar system for monitoring spatial distribution and elemental analyses by X-Ray Fluorescence and Proton Elastic Scattering.