Multi element particle detection and information gain from particle clustering: A case study of waste water treatment plants across Switzerland
Single-particle inductively coupled plasma time-of-flight mass spectrometer (sp-ICP-TOFMS) is a powerful tool for multiplex nanoparticle characterization. With the combination of online microdroplet calibration1 and uptake standard 2 one can measure nanoparticle almost in the whole periodic table considering limit of detection on individual elements. Conventional sp-ICP-TOFMS are user intensive and one tries to look into data to find particle and pattern, but such method is time-consuming, not scalable and prone to miss many particle types. Apart from its analytical challenges, question still remains is how to perform multi elemental particle analysis and obtain further information such as particles sources in the sample. Here we present a new approach to analyzing multi-element sp-ICP-TOFMS data in order to measure particles also find possible clusters of multi-element particles in each and across samples. Some critical step includes, autonomously looking for signal corresponding to particles in data and calibrate it to corresponding mass of particle using online microdroplet calibration, corrected for falsely indicated multi-elemental particles2 and cluster them to separate group base on their elemental and mass fingerprint. As case study analyzed five different wastewater treatment plants (WWTP) influent and effluent across Switzerland. WWTP samples are chosen for their high complexity and limited knowledge about their particulate fraction. Besides looking at important questions such as how efficient is each WWTP to remove the particles, we also investigate the source of different particulate contaminants in such samples. A variety of single and multi-elemental particles were detected and measured for their mass and concentration. Furthermore, clustering recognized some conserved classes of particle across different WWTP with natural origin. Some other classes indicated as anthropogenic and need further multidisciplinary effort to find their origin.
[1] Lyndsey Hendriks, Benita Ramkorun-Schmidt, Alexander Gundlach-Graham, Julian Koch, Robert N. Grass, Norbert Jakubowski, and Detlef Günther, Journal of Analytical Atomic Spectrometry, 2019, 34, 716-28.
[2] Kamyar Mehrabi, Detlef Günther, and Alexander Gundlach-Graham, Environmental Science: Nano, 2019, 6, 3349-58.