In Situ Characterization of Optical Absorption by Carbonaceous Aerosols: Calibration and Measurement

Light absorption by aerosols has a great impact on climate change. A Photoacoustic spectrometer (PA) coupled with aerosol-based classification techniques represents an in situ method that can quantify the light absorption by aerosols in a real time, yet significant differences have been reported using this method versus filter based methods or the so-called difference method based upon light extinction and light scattering measurements. This dissertation focuses on developing calibration techniques for instruments used in measuring the light absorption cross section, including both particle diameter measurements by the differential mobility analyzer (DMA) and light absorption measurements by PA. Appropriate reference materials were explored for the calibration/validation of both measurements. The light absorption of carbonaceous aerosols was also investigated to provide fundamental understanding to the absorption mechanism. The first topic of interest in this dissertation is the development of calibration nanoparticles. In this study, bionanoparticles were confirmed to be a promising reference material for particle diameter as well as ion-mobility. Experimentally, bionanoparticles demonstrated outstanding homogeneity in mobility compared to currently used calibration particles. A numerical method was developed to calculate the true distribution and to explain the broadening of measured distribution. The high stability of bionanoparticles was also confirmed. For PA measurement, three aerosol with spherical or near spherical shapes were investigated as possible candidates for a reference standard: C60, copper and silver. Comparisons were made between experimental photoacoustic absorption data with Mie theory calculations. This resulted in the identification of C60 particles with a mobility diameter of 150 nm to 400 nm as an absorbing standard at wavelengths of 405 nm and 660 nm. Copper particles with a mobility diameter of 80 nm to 300 nm are also shown to be a promising reference candidate at wavelength of 405 nm. The second topic of this dissertation focuses on the investigation of light absorption by carbonaceous particles using PA. Optical absorption spectra of size and mass selected laboratory generated aerosols consisting of black carbon (BC), BC with non-absorbing coating (ammonium sulfate and sodium chloride) and BC with a weakly absorbing coating (brown carbon derived from humic acid) were measured across the visible to near-IR (500 nm to 840 nm). The manner in which BC mixed with each coating material was investigated. The absorption enhancement of BC was determined to be wavelength dependent. Optical absorption spectra were also taken for size and mass selected smoldering smoke produced from six types of commonly seen wood in a laboratory scale apparatus.

Multi-sensor Cloud and Aerosol Retrieval Simulator and Its Applications

Executing a cloud or aerosol physical properties retrieval algorithm from controlled synthetic data is an important step in retrieval algorithm development. Synthetic data can help answer questions about the sensitivity and performance of the algorithm or aid in determining how an existing retrieval algorithm may perform with a planned sensor. Synthetic data can also help in solving issues that may have surfaced in the retrieval results. Synthetic data become very important when other validation methods, such as field campaigns,are of limited scope. These tend to be of relatively short duration and often are costly. Ground stations have limited spatial coverage whilesynthetic data can cover large spatial and temporal scales and a wide variety of conditions at a low cost. In this work I develop an advanced cloud and aerosol retrieval simulator for the MODIS instrument, also known as Multi-sensor Cloud and Aerosol Retrieval Simulator (MCARS). In a close collaboration with the modeling community I have seamlessly combined the GEOS-5 global climate model with the DISORT radiative transfer code, widely used by the remote sensing community, with the observations from the MODIS instrument to create the simulator. With the MCARS simulator it was then possible to solve the long standing issue with the MODIS aerosol optical depth retrievals that had a low bias for smoke aerosols. MODIS aerosol retrieval did not account for effects of humidity on smoke aerosols. The MCARS simulator also revealed an issue that has not been recognized previously, namely,the value of fine mode fraction could create a linear dependence between retrieved aerosol optical depth and land surface reflectance. MCARS provided the ability to examine aerosol retrievals against “ground truth” for hundreds of thousands of simultaneous samples for an area covered by only three AERONET ground stations. Findings from MCARS are already being used to improve the performance of operational MODIS aerosol properties retrieval algorithms. The modeling community will use the MCARS data to create new parameterizations for aerosol properties as a function of properties of the atmospheric column and gain the ability to correct any assimilated retrieval data that may display similar dependencies in comparisons with ground measurements.