Nontarget Chemical Composition of Surface Waters May Reflect Ecosystem Processes More than Discrete Source Contributions.

We investigated environmental, landscape, and microbial factors that could structure the spatiotemporal variability in the nontarget chemical composition of four riverine systems in the Oregon Coast Range, USA. We hypothesized that the nontarget chemical composition in river water would be structured by broad-scale landscape gradients in each watershed. Instead, only a weak relationship existed between the nontarget chemical composition and land cover gradients.

Machine Learning Applications for Chemical Fingerprinting and Environmental Source Tracking Using Non-target Chemical Data.

A frequent goal of chemical forensic analyses is to select a panel of diagnostic chemical features─colloquially termed a chemical fingerprint─that can predict the presence of a source in a novel sample. However, most of the developed chemical fingerprinting workflows are qualitative in nature. Herein, we report on a quantitative machine learning workflow.