@misc{9240404,
  abstract     = {{Greenhouse gases and light-absorbing particles in the atmosphere, including soot, play a key role in climate change. To understand the effect such small particles have on the climate, we first need to understand how they form and how they behave. Soot particles are produced from incomplete combustion processes of hydrocarbons, forming a mixture of graphitic and amorphous structures instead of carbon dioxide. Soot properties depend on combustion conditions, such as fuel type, temperature, and pressure. Many experiments have been conducted in a laboratory environment to understand the formation and properties of soot produced under different combustion conditions. Soot compositions can be inferred from their Raman spectra and the fluorescence emissions. Many spectroscopic techniques have been developed and applied widely in the lab scale, but not in naturally occurring conditions. For this reason, we aim to construct one for a atmospheric application based on the Scheimpflug principle and Raman scattering that is called Scheimpflug Raman Lidar (SRL). The Scheimpflug lidar technique has been used in many studies of insects, vegetation, and aquatic life. In the SRL, we use a high-power continuous-wave laser rather than a pulsed one. A simulation model was created prior to the theoretical model, which was optimized to resolve the Raman signal of soot. We successfully adapted the optimized construction and tested it on black soot (OP1 soot) and brown soot (OP6 soot) generated by a mini-CAST soot generator. To remove air contributions from these soot spectra, we combined SRL with polarization effects and Fast Fourier Transform (FFT) theory. By collecting data at various polarization angles, a FFT separated the unpolarized Raman signal of soot from the polarized air contributions. This split did not improve the Raman signal of soot, but it was able to identify all polarized contributions within the Raman spectrum, such as carbon dioxide, oxygen, nitrogen, and water vapor. This technique can thus be used to identify what gases are part of the combustion process.}},
  author       = {{Dahlberg, Liam}},
  language     = {{eng}},
  note         = {{Student Paper}},
  title        = {{Construction of a hyperspectral Scheimpflug lidar for soot characterization in the aerosol phase}},
  year         = {{2026}},
}