Soot and other products of incomplete combustion play an important role in the chemistry of the atmosphere. As particles are exposed to trace gases, such as ozone, their chemistry and physical properties can be altered leading to changes in their optical properties, as well as their cloud condensation nuclei and ice nucleation abilities. These alterations can lead to changes in the global radiative budget and cloud microphysical processes, which in turn affect the climate. In this study, the chemical and physical changes associated with the oxidation of pyrene, anthracene, and carbon (lampblack) by ozone were investigated. Fourier Transform Infrared Spectroscopy was used to identify oxidation products and track reaction progress for these representative aerosols. A C=O band attributed to a carboxylic acid formation was observed for all three substances, at each level of exposure to ozone - 20 ppm, 40 ppm, and 80 ppm. Second order reaction rate constants ranged from 9.58 x 10-16 cm2 molecules-1 s-1 to 7.71 x 10-13 cm2 molecules-1 s-1. Measurements of water uptake, ice nucleation efficiency, and optical properties were obtained to determine whether any physical changes associated with the oxidation process occurred. Optical measurements show an increase in the ultra-violet absorption of anthracene, but not for pyrene, while an increase in the visible absorption for pyrene was observed, but not for anthracene. Oxidized soot froze at a warmer temperature (-22.8 degrees C) then fresh soot (-25.6 degrees C), showing an increase in ice nucleation efficiency. Our data indicates that oxidation by ozone does alter the chemistry and physical properties of the substances study, leading to possible changes in how they interact with atmospheric processes.

This research focuses on aircraft observational studies of aerosol-cloud interactions in cumulus clouds. The data were collected in the summer of 2004, the spring of 2007 and the mid-winter and spring of 2008 in Texas, central Saudi Arabia and Istanbul, Turkey, respectively. A set of 24 pairs of sub-cloud aerosol and cloud penetration data are analyzed. Measurements of fine and coarse mode aerosol concentrations from 3 different instruments were combined and fitted with lognormal distributions. The fit parameters of the lognormal distributions are compared with cloud droplet effective radii retrieved from 260 cloud penetrations. Cloud condensation nuclei (CCN) measurements for a subset of 10 cases from the Istanbul region are compared with concentrations predicted from aerosol size distributions. Ammonium sulfate was assumed to represent the soluble component of aerosol with dry sizes smaller than 0.5 mm and sodium chloride for aerosol larger than 0.5 mm. The measured CCN spectrum was used to estimate the soluble fraction. The correlations of the measured CCN concentration with the predicted CCN concentration were strong (R2 > 0.89) for supersaturations of 0.2, 0.3 and 0.6%. The measured concentrations were typically consistent with an aerosol having a soluble fraction between roughly 0.5 and 1.0, suggesting a contribution of sulfate or some other similarly soluble inorganic compound. The predicted CCN were found to vary by +or-3.7% when the soluble fraction was varied by 0.1. Cumulative aerosol concentrations at cutoff dry diameters of 1.1, 0.1 and 0.06 mm were found to be correlated with cloud condensation nuclei concentrations but not with maximum cloud base droplet concentrations. It is also shown that in some cases the predominant mechanisms involved in the formation of precipitation were altered and modified by the aerosol properties. This study suggests that CCN-forced variations in cloud droplet number concentration can change the effective radius profile and the type of precipitation hydrometeors. These differences may have a major impact on the global hydrological cycle and energy budget.

Content Centric Networking (CCN) is a novel networking architecture in which communication is resolved based on names, or descriptions of the data transferred instead of addresses of the end-hosts. While CCN demonstrates many promising potentials, its current implementation suffers from severe performance limitations. In this thesis we study the performance and analyze the bottleneck of the existing CCN prototype. Based on the analysis, a variety of design alternatives are proposed for realizing high performance content centric networking over virtual infrastructure. Preliminary implementations for two of the approaches are developed and evaluated on Smart Applications on Virtual Infrastructure (SAVI) testbed. The evaluation results demonstrate that our design is capable of providing scalable content centric routing solution beyond 1Gbps throughput under realistic traffic load.

Content Centric Networking (CCN) is a novel networking architecture in which communication is resolved based on names, or descriptions of the data transferred instead of addresses of the end-hosts. While CCN demonstrates many promising potentials, its current implementation suffers from severe performance limitations. In this thesis we study the performance and analyze the bottleneck of the existing CCN prototype. Based on the analysis, a variety of design alternatives are proposed for realizing high performance content centric networking over virtual infrastructure. Preliminary implementations for two of the approaches are developed and evaluated on Smart Applications on Virtual Infrastructure (SAVI) testbed. The evaluation results demonstrate that our design is capable of providing scalable content centric routing solution beyond 1Gbps throughput under realistic traffic load.

The feedbacks among aerosols, clouds, and radiation are important components for understanding Earth's climate system and quantifying human-induced climate change, yet the magnitude of these feedbacks remain highly uncertain. Since every cloud droplet in the atmosphere begins with water condensing on a pre-existing aerosol particle, characterizing the ability of aerosols to uptake water vapor and form cloud condensation nuclei (CCN) are key to understanding the microphysics behind cloud formation, as well as assess the impact aerosols have on the Earth system. Through a combination of controlled laboratory experiments and field measurements, this thesis characterizes the ability of atmospheric aerosols to uptake water vapor and become CCN at controlled levels of water vapor supersaturation. The origin of the particle water uptake, termed hygroscopicity, is also explored, being from either the presence of deliquescent soluble material and/or adsorption onto insoluble surfaces. The data collected and presented is comprehensive and includes (1) ground samples of volcanic ash, collected from six recent eruptions re-suspended in the laboratory for analysis, (2) laboratory chamber and flow-tube studies on the oxidation and uptake of surface active organic compounds, and (3) in-situ aircraft measurements of aerosols from the Arctic background, Canadian boreal forests, fresh and aged biomass burning, anthropogenic industrial pollution, and from within tropical cyclones in the Atlantic basin. Having a more thorough understanding of aerosol water uptake will enable more accurate representation of cloud droplet number concentrations in global models, which can have important implications on reducing the uncertainty of aerosol-cloud-climate interactions, as well as additional uncertainties in aerosol transport, atmospheric lifetime, and impact on storm dynamics.

No description available.

The satellite-based cloud condensation nuclei (CCN) proxies used to quantify the aerosolcloud interactions (ACIs) are column integrated and do not guarantee the vertical co-location of aerosols and clouds. This has encouraged the use of height-resolved measurements of spaceborne lidars for ACI studies and led to advancements in lidar-based CCN retrieval algorithms. In this study, we present a comparison between the number concentration of CCN (nCCN) derived from ground-based in situ and spaceborne lidar cloud-aerosol lidar with orthogonal polarization (CALIOP) measurements. On analysing their monthly time series, we found that about 88% of CALIOP nCCN estimates remained within a factor of 1.5 of the in situ measurements. Overall, the CALIOP estimates of monthly nCCN were in good agreement with the in situ measurements with a normalized mean error of 71%, normalized mean bias of 39% and correlation coefficient of 0.68. Based on our comparison results, we point out the necessary measures that should be considered for global nCCN retrieval. Our results show the competence of CALIOP in compiling a global height- and type-resolved nCCN dataset for use in ACI studies.

It has been historically assumed that most of the uncertainty associated with the aerosol indirect effect on climate can be attributed to the unpredictability of updrafts. We assess the sensitivity of cloud droplet number density to realistic variations in aerosol chemical properties and to variable updraft velocities using a 1-dimensional cloud parcel model. The results suggest that aerosol chemical variability may be as important to the aerosol indirect effect as the effect of unresolved cloud dynamics, especially in polluted environments. We next used a continuous flow streamwise thermal gradient Cloud Condesnation Nuclei counter (CCNc) to study the water-uptake properties of the ambient aerosol, by exposing an aerosol sample to a controlled water vapor supersaturation and counting the resulting number of droplets. The heat transfer properties and droplet growth within the CCNc were first modeled and experimentally characterized. We describe results from the MIRAGE field campaign at a ground-based site during March, 2006. Size-resolved CCN activation spectra and hygroscopic growth factor distributions of the ambient aerosol in Mexico City were obtained, and an analytical technique was developed to quantify a probability distribution of solute volume fractions for the CCN, as well as the aerosol mixing-state. The CCN were shown to be much less CCN active than ammonium sulfate, with water uptake properties more consistent with low molecular weight organic compounds. We also describe results from the GoMACCS field study, an airborne field campaign in Houston, Texas during August-September, 2006. GoMACCS tested our ability to predict CCN for highly polluted conditions with limited chemical information. Assuming the particles were composed purely of ammonium sulfate, CCN closure was obtained with a 10% overprediction bias on average for CCN concentrations ranging from less than 100 cm-3 to over 10,000 cm-3, but with on average 50% variability. Assuming measured concentrations of organics to be internally mixed and insoluble tended to reduce the overprediction bias for less polluted conditions, but led to underprediction bias in the most polluted conditions. Comparing the two campaigns, it is clear that the chemistry of the particles plays an important role in our ability to predict CCN concentrations.

Phonological awareness is the ability to recognize, reflect on and manipulate sound structures of a language. This ability has been shown to be crucial when acquiring literacy. The PhonicStick is a speech-generation communication device, which was initially developed for individuals with complex communication needs (CCN) though more recent research has focused on the effects of the device on factors important for literacy acquisition. In the present study the effects on phonological awareness were evaluated after seven group training sessions with the PhonicStick. The participants of the study were 20 typically developing South African 5-6 year old children. All participants where pre and post tested with The Phonological Awareness Test part c) isolation and a PhonicStick test which tested the ability to produce isolated phonemes and combinations of three phonemes with the device. The results of the study showed that training with the PhonicStick did not appear to improve results on The Phonological Awareness Test part c) isolation. However, it was found that the participants of the training group had improved their ability to manoeuvre the PhonicStick and to produce isolated phonemes and combinations of three phonemes. / Fonologisk medvetenhet är förmågan att känna igen, reflektera över och manipulera ett språks ljudstrukturer. Denna förmåga har visat sig vara betydelsefull vid tillägnandet av läs- och skrivförmåga. The PhonicStick är ett talgenererande kommunikationshjälpmedel som ursprungligen utformades för individer med komplexa kommunikationsbehov. Senare forskning har även fokuserat på hjälpmedlets effekter på faktorer som är viktiga vid tillägnandet av läs- och skrivförmåga. I föreliggande studie utvärderades effekterna på fonologisk medvetenhet hos 20 normalutvecklade sydafrikanska barn i åldrarna 5-6 år efter sju gruppträningstillfällen med the PhonicStick. Alla deltagare i studien pre- och posttestades med två test. Deltest c) från The Phonological Awareness Test rörande förmågan att isolera ljud, samt ett PhonicStick test. Detta testade förmågan att producera isolerade fonem och kombinationer bestående av tre fonem med the PhonicStick. Studiens resultat visade att träning med the PhonicStick inte resulterade i förbättrat resultat på The Phonological Awareness Test del c) isolerade fonem. Däremot tydde resultatet på att deltagarna i testgruppen förbättrade sin förmåga att styra the PhonicStick samt producera isolerade fonem och fonemkombinationer bestående av tre fonem.

Anthropogenic atmospheric aerosols (suspended particulate matter) can modify the radiative balance (and climate) of the Earth by altering the properties and global distribution of clouds. Current climate models however cannot adequately account for many important aspects of these aerosol-cloud interactions, ultimately leading to a large uncertainty in the estimation of the magnitude of the effect of aerosols on climate. This thesis focuses on the development of physically-based descriptions of aerosol-cloud processes in climate models that help to address some of such predictive uncertainty. It includes the formulation of a new analytical parameterization for the formation of ice clouds, and the inclusion of the effects of mixing and kinetic limitations in existing liquid cloud parameterizations. The parameterizations are analytical solutions to the cloud ice and water particle nucleation problem, developed within a framework that considers the mass and energy balances associated with the freezing and droplet activation of aerosol particles. The new frameworks explicitly account for the impact of cloud formation dynamics, the aerosol size and composition, and the dominant freezing mechanism (homogeneous vs. heterogeneous) on the ice crystal and droplet concentration and size distribution. Application of the new parameterizations is demonstrated in the NASA Global Modeling Initiative atmospheric and chemical and transport model to study the effect of aerosol emissions on the global distribution of ice crystal concentration, and, the effect of entrainment during cloud droplet activation on the global cloud radiative properties. The ice cloud formation framework is also used within a parcel ensemble model to understand the microphysical structure of cirrus clouds at very low temperature. The frameworks developed in this work provide an efficient, yet rigorous, representation of cloud formation processes from precursor aerosol. They are suitable for the study of the effect of anthropogenic aerosol emissions on cloud formation, and can contribute to the improvement of the predictive ability of atmospheric models and to the understanding of the impact of human activities on climate.