Evaluating PM 2.5 element concentration measurements for a nationwide monitoring network.

Journal of the Air & Waste Management Association (1995)(2023)

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摘要
Particulate matter (PM) concentrations have decreased dramatically over the past 20 years, thus lower method detection limits (MDL) are required for these measurements. Energy-dispersive X-ray fluorescence (XRF) spectroscopy is used to quantify multiple elements simultaneously in the United States Environmental Protection Agency (US EPA) Chemical Speciation Network (CSN). Inductively-coupled plasma mass spectrometry (ICP-MS) is an alternative analysis with lower MDL for elements. Here, we present a side-by-side comparison of XRF and ICP-MS for elements in PM samples collected via the US EPA's CSN. For ICP-MS, a simple extraction and ICP-MS analysis technique was applied to a wide variety of samples to minimize effort and cost and serve as a feasibility test for a large monitoring network. Filter samples ( = 549) from various urban locations across the US were analyzed first analyzed via XRF at UC Davis and then ICP-MS at RTI International. Both methods measured 29 of the same elements out of the 33 usually reported to CSN. Of these 29, 14 elements (Na, Mg, Al, K, Ca, Ti, V, Cr, Mn, Fe, Ni, Cu, Zn, Pb) were found to be frequently detected (i.e. had more than 10% of values above both XRF and ICP-MS MDL). ICP-MS was found to have lower MDL for 26 out of 29 elements, namely Na, Mg, Al, Ca, Ti, V, Cr, Mn, Fe, Co, Ni, Cu, As, Se, Rb, Sr, Zr, Ag, Cd, In, Sn, Sb, Cs, Ba, Ce, Pb; conversely, XRF had lower MDL for 3 elements, namely, P, K, Zn. Intra-method quality checks using (1) inter-elemental inspection of scatter plots using knowledge of element sources and (2) scatter plots of routine versus collocated measurements reveal that ICP-MS exhibits better measurement precision. Lower detection limits for element measurements in nationwide PM monitoring networks would benefit human-health and source apportionment research.
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关键词
element concentration measurements,monitoring
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