What is he best known for?
The fields of study he is best known for:
- Thermodynamics
- Aerosol
- Carbon dioxide
Daniel A. Lack mostly deals with Absorption, Aerosol, Soot, Atmospheric sciences and Atmosphere.
Daniel A. Lack focuses mostly in the field of Absorption, narrowing it down to matters related to Mie scattering and, in some cases, Mixing ratio and Stratosphere.
His Aerosol study combines topics from a wide range of disciplines, such as Detection limit and Photoacoustic spectroscopy.
The Atmospheric sciences study combines topics in areas such as Radiative transfer, Meteorology and Arctic.
The various areas that Daniel A. Lack examines in his Radiative transfer study include Climate change mitigation and Climate model.
His Atmosphere research is multidisciplinary, incorporating perspectives in Mixing and Radiative forcing.
His most cited work include:
- Radiative Absorption Enhancements Due to the Mixing State of Atmospheric Black Carbon (405 citations)
- Radiative Absorption Enhancements Due to the Mixing State of Atmospheric Black Carbon (405 citations)
- Impact of brown and clear carbon on light absorption enhancement, single scatter albedo and absorption wavelength dependence of black carbon (285 citations)
What are the main themes of his work throughout his whole career to date?
Daniel A. Lack focuses on Aerosol, Atmospheric sciences, Absorption, Analytical chemistry and Meteorology.
His Aerosol research incorporates elements of Air quality index, Relative humidity, Spectrometer and Extinction.
His research in Atmospheric sciences intersects with topics in Atmosphere and Radiative forcing.
Daniel A. Lack undertakes multidisciplinary investigations into Absorption and Soot in his work.
His Analytical chemistry study also includes fields such as
- Mineralogy together with Optical property,
- Absorption angstrom exponent most often made with reference to Visible spectrum.
Meteorology and Radiative transfer are commonly linked in his work.
He most often published in these fields:
- Aerosol (93.58%)
- Atmospheric sciences (69.72%)
- Absorption (62.39%)
What were the highlights of his more recent work (between 2014-2018)?
- Atmospheric sciences (69.72%)
- Aerosol (93.58%)
- Absorption (62.39%)
In recent papers he was focusing on the following fields of study:
Atmospheric sciences, Aerosol, Absorption, Trace gas and Analytical chemistry are his primary areas of study.
Daniel A. Lack interconnects Atmosphere, Meteorology and Oil shale in the investigation of issues within Atmospheric sciences.
His work deals with themes such as In situ and Refractive index, which intersect with Aerosol.
He studies Single-scattering albedo, a branch of Absorption.
The concepts of his Trace gas study are interwoven with issues in Relative humidity and Extinction.
His biological study spans a wide range of topics, including Angstrom exponent and Mie scattering.
Between 2014 and 2018, his most popular works were:
- Parameterization of Single Scattering Albedo (SSA) and Absorption Angstrom Exponent (AAE) with EC/OC for Aerosol Emissions from Biomass Burning (72 citations)
- Aerosol optical properties in the southeastern United States in summer – Part 1: Hygroscopic growth (60 citations)
- Aerosol optical properties in the southeastern United States in summer – Part 1: Hygroscopic growth (60 citations)
In his most recent research, the most cited papers focused on:
- Thermodynamics
- Carbon dioxide
- Meteorology
His scientific interests lie mostly in Atmospheric sciences, Aerosol, Meteorology, Absorption and Trace gas.
Daniel A. Lack combines subjects such as Atmosphere and Oil shale with his study of Atmospheric sciences.
His studies in Aerosol integrate themes in fields like Albedo and Earth's energy budget.
Daniel A. Lack has included themes like Daytime and Transect in his Meteorology study.
His Absorption research includes elements of Angstrom exponent, Visible spectrum, Refractive index and Analytical chemistry.
His Trace gas study incorporates themes from Aerosol composition, Aerodynamic diameter, Extinction, Planetary boundary layer and Relative humidity.
This overview was generated by a machine learning system which analysed the scientist’s
body of work. If you have any feedback, you can
contact us
here.
