Articles | Volume 13, issue 10
https://doi.org/10.5194/amt-13-5369-2020
https://doi.org/10.5194/amt-13-5369-2020
Research article
 | 
09 Oct 2020
Research article |  | 09 Oct 2020

Quantification of toxic metals using machine learning techniques and spark emission spectroscopy

Seyyed Ali Davari and Anthony S. Wexler

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Short summary
Traditional instruments for detection and quantification of toxic metals in the atmosphere are expensive. In this study, we have designed, fabricated, and tested a low-cost instrument, which employs cheap components to detect and quantify toxic metals. Advanced machine learning (ML) techniques have been used to improve the instrument's performance. This study demonstrates how the combination of low-cost sensors with ML can address problems that traditionally have been too expensive to be solved.