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Painting a More Colorful Picture of the Atmosphere: Hyperspectral Lidar for Characterization of Atmospheric Constituents

Engman, Hugo LU (2026) FYSM64 20261
Department of Physics
Combustion Physics
Abstract
Atmospheric particles play a significant role in radiative forcing through light scattering and new methods are called for to better characterize their impact. Typical Lidar systems emit single wavelength light, not utilizing full spectral information from scattering measurements.

This thesis aims to use a hyperspectral lidar system to measure the spectral dependence of scattering and absorption of different atmospheric constituents. This was done by emitting broad band short-wave infrared light and collecting the backscattered light on a 2D InGaAs detector, mapping wavelength on one axis and range on the other.

The system was tested along a horizontal path over a range of 700 meters, where ambient measurements were made under... (More)
Atmospheric particles play a significant role in radiative forcing through light scattering and new methods are called for to better characterize their impact. Typical Lidar systems emit single wavelength light, not utilizing full spectral information from scattering measurements.

This thesis aims to use a hyperspectral lidar system to measure the spectral dependence of scattering and absorption of different atmospheric constituents. This was done by emitting broad band short-wave infrared light and collecting the backscattered light on a 2D InGaAs detector, mapping wavelength on one axis and range on the other.

The system was tested along a horizontal path over a range of 700 meters, where ambient measurements were made under different atmospheric conditions as well as controlled releases of aerosol plumes. The system successfully retrieved hyperspectral signals from multiple atmospheric constituents which revealed spectral features in absorption and scattering. From these measurements, wavelength dependent backscatter and attenuation coefficients could be calculated.

The study demonstrates the capability of the hyperspectral lidar to characterize particulate matter for a broadband spectrum, which can provide information on microphysical properties. The broad applicability of the method showcased the possibility to measure simultaneous backscatter and absorption for different spectral bands, supporting future applications in atmospheric monitoring studies. (Less)
Popular Abstract
Have you ever noticed how red and pretty the sunsets appear in large cities? This is the result of aerosols, small particles suspended within the air, filtering the light over large distances. Aerosols in cities are often the result of pollution, while natural aerosols also appear in the form of pollen, sea spray and sand dust. They are all around us, and even though they are often too small to observe directly, they leave noticeable traces in the way they interact with light.

As it turns out, these particles have a big impact on us humans. They can have adverse effects on the respiratory system since they are small and easily inhaled. They also affect the climate where their interactions with light play a big role. While greenhouse... (More)
Have you ever noticed how red and pretty the sunsets appear in large cities? This is the result of aerosols, small particles suspended within the air, filtering the light over large distances. Aerosols in cities are often the result of pollution, while natural aerosols also appear in the form of pollen, sea spray and sand dust. They are all around us, and even though they are often too small to observe directly, they leave noticeable traces in the way they interact with light.

As it turns out, these particles have a big impact on us humans. They can have adverse effects on the respiratory system since they are small and easily inhaled. They also affect the climate where their interactions with light play a big role. While greenhouse gases heat the Earth by absorbing its outgoing thermal radiation, aerosols primarily scatter incoming sunlight and can thus have a cooling effect. But since there are many different types of aerosols in our atmosphere, their effect on the climate is uncertain.

How do we then study these tiny particles? As it is not always an option to look at them up close, one has to turn to remote sensing. One of the primary remote sensing techniques/instruments is Lidar (Light detection and ranging). The working principle is to emit a laser and measure how it interacts with particles and molecules in its path. One can then try to piece together which aerosols are present in the air. This is, however, a daunting task as a laser of one wavelength does not provide enough information about the particles. Simply put, one is left with more questions than answers.

This problem is usually solved by incorporating a couple of more wavelengths in different ways. Consider then if we replace a few monochromatic light sources with a complete continuous wavelength spectrum: a supercontinuum. This would give complete information about the scattering properties of the aerosols. In this thesis project, I have demonstrated the capabilities of such a light source together with a receiver able to resolve both distance and wavelength in a hyperspectral Lidar.

To do this, I have conducted measurements on the ambient aerosols in Lund as well as controlled plumes of aerosols. By adjusting the parameters of the instrument and filtering and analysing the data, I investigated the benefits as well as the limitations of the hyperspectral Lidar. The study showed that fog, aerosol clouds, snowflakes and plumes can indeed be resolved. By obtaining higher precision, one could measure even finer aerosols, which would be ideal for atmospheric measurements.

In the future, one might hope for an instrument such as this to be placed on a satellite to measure aerosols throughout the atmosphere, all around the world. This is a formidable task, but if completed, a full spectral image of all aerosols could be collected and we could determine the full scope of the impact of aerosols on our planet. (Less)
Please use this url to cite or link to this publication:
author
Engman, Hugo LU
supervisor
organization
course
FYSM64 20261
year
type
H2 - Master's Degree (Two Years)
subject
keywords
Hyperspectral, Lidar, Supercontinuum, Aerosols
language
English
id
9241831
date added to LUP
2026-06-28 11:26:13
date last changed
2026-06-28 11:26:13
@misc{9241831,
  abstract     = {{Atmospheric particles play a significant role in radiative forcing through light scattering and new methods are called for to better characterize their impact. Typical Lidar systems emit single wavelength light, not utilizing full spectral information from scattering measurements.

This thesis aims to use a hyperspectral lidar system to measure the spectral dependence of scattering and absorption of different atmospheric constituents. This was done by emitting broad band short-wave infrared light and collecting the backscattered light on a 2D InGaAs detector, mapping wavelength on one axis and range on the other.

The system was tested along a horizontal path over a range of 700 meters, where ambient measurements were made under different atmospheric conditions as well as controlled releases of aerosol plumes. The system successfully retrieved hyperspectral signals from multiple atmospheric constituents which revealed spectral features in absorption and scattering. From these measurements, wavelength dependent backscatter and attenuation coefficients could be calculated.

The study demonstrates the capability of the hyperspectral lidar to characterize particulate matter for a broadband spectrum, which can provide information on microphysical properties. The broad applicability of the method showcased the possibility to measure simultaneous backscatter and absorption for different spectral bands, supporting future applications in atmospheric monitoring studies.}},
  author       = {{Engman, Hugo}},
  language     = {{eng}},
  note         = {{Student Paper}},
  title        = {{Painting a More Colorful Picture of the Atmosphere: Hyperspectral Lidar for Characterization of Atmospheric Constituents}},
  year         = {{2026}},
}