Source Apportionment of Environmental Combustion Sources using Excitation Emission Matrix Fluorescence Spectroscopy and Machine Learning.

ABSTRACT: The link between particulate matter (PM) air pollution and negative health effects is well-established. Air pollution was estimated to cause 4.9 million deaths in 2017 and PM was responsible for 94% of these deaths. In order to inform effective mitigation strategies in the future, further study of PM and its health effects is important. Here, we present a method for identifying sources of combustion generated PM using excitation-emission matrix (EEM) fluorescence spectroscopy and machine learning (ML) algorithms. PM samples were collected during a health effects exposure assessment panel study in Seattle. We use archived field samples from the exposure study and the associated positive matrix factorization (PMF) source apportionment based on X-ray fluorescence and light absorbing carbon me

SUBMITTER: Rutherford JW 

PROVIDER: S-EPMC8312701 | biostudies-literature | 2021 Aug

REPOSITORIES: biostudies-literature