Articles | Volume 15, issue 8
https://doi.org/10.5194/amt-15-2591-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-15-2591-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
29 Apr 2022
Research article |
| 29 Apr 2022
| 29 Apr 2022
Development and application of a supervised pattern recognition algorithm for identification of fuel-specific emissions profiles
Christos Stamatis
Department of Chemical and Environmental Engineering and College of Engineering – Center for Environmental Research and Technology (CE-CERT), University of California, Riverside, Riverside, CA, USA
Kelley Claire Barsanti
CORRESPONDING AUTHOR
Department of Chemical and Environmental Engineering and College of Engineering – Center for Environmental Research and Technology (CE-CERT), University of California, Riverside, Riverside, CA, USA
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Short summary
Building on the identification of hundreds of gas-phase chemicals in smoke samples from laboratory and field studies, an algorithm was developed that successfully identified chemical patterns that were consistent among types of trees and unique between types of trees that are common fuels in western coniferous forests. The algorithm is a promising approach for selecting chemical speciation profiles for air quality modeling using a highly reduced suite of measured compounds.
Building on the identification of hundreds of gas-phase chemicals in smoke samples from...
