Microscopic and spectroscopic analysis of biogenic aerosols

Aerosol particles are important actors in the Earth’s atmosphere and climate system. They scatter and absorb sunlight, serve as nuclei for water droplets and ice crystals in clouds and precipitation, and are a subject of concern for public health. Atmospheric aerosols originate from both natural and anthropogenic sources, and emissions resulting from human activities have the potential to influence the hydrological cycle and climate. An assessment of the extent and impacts of this human force requires a sound understanding of the natural aerosol background. This dissertation addresses the composition, properties, and atmospheric cycling of biogenic aerosol particles, which represent a major fraction of the natural aerosol burden. The main focal points are: (i) Studies of the autofluo-rescence of primary biological aerosol particles (PBAP) and its application in ambient measure-ments, and (ii) X-ray microscopic and spectroscopic investigations of biogenic secondary organic aerosols (SOA) from the Amazonian rainforest.rnAutofluorescence of biological material has received increasing attention in atmospheric science because it allows real-time monitoring of PBAP in ambient air, however it is associated with high uncertainty. This work aims at reducing the uncertainty through a comprehensive characterization of the autofluorescence properties of relevant biological materials. Fluorescence spectroscopy and microscopy were applied to analyze the fluorescence signatures of pure biological fluorophores, potential non-biological interferences, and various types of reference PBAP. Characteristic features and fingerprint patterns were found and provide support for the operation, interpretation, and further development of PBAP autofluorescence measurements. Online fluorescence detection and offline fluorescence microscopy were jointly applied in a comprehensive bioaerosol field measurement campaign that provided unprecedented insights into PBAP-linked biosphere-atmosphere interactions in a North-American semi-arid forest environment. Rain showers were found to trigger massive bursts of PBAP, including high concentrations of biological ice nucleators that may promote further precipitation and can be regarded as part of a bioprecipitation feedback cycle in the climate system. rnIn the pristine tropical rainforest air of the Amazon, most cloud and fog droplets form on bio-genic SOA particles, but the composition, morphology, mixing state and origin of these particles is hardly known. X-ray microscopy and spectroscopy (STXM-NEXAFS) revealed distinctly different types of secondary organic matter (carboxyl- vs. hydroxy-rich) with internal structures that indicate a strong influence of phase segregation, cloud and fog processing on SOA formation, and aging. In addition, nanometer-sized potassium-rich particles emitted by microorganisms and vegetation were found to act as seeds for the condensation of SOA. Thus, the influence of forest biota on the atmospheric abundance of cloud condensation nuclei appears to be more direct than previously assumed. Overall, the results of this dissertation suggest that biogenic aerosols, clouds and precipitation are indeed tightly coupled through a bioprecipitation cycle, and that advanced microscopic and spectroscopic techniques can provide detailed insights into these mechanisms.rn

Software tools and efficient algorithms for the feature detection, feature tracking, event localization, and visualization of large sets of atmospheric data

Data sets describing the state of the earth's atmosphere are of great importance in the atmospheric sciences. Over the last decades, the quality and sheer amount of the available data increased significantly, resulting in a rising demand for new tools capable of handling and analysing these large, multidimensional sets of atmospheric data. The interdisciplinary work presented in this thesis covers the development and the application of practical software tools and efficient algorithms from the field of computer science, aiming at the goal of enabling atmospheric scientists to analyse and to gain new insights from these large data sets. For this purpose, our tools combine novel techniques with well-established methods from different areas such as scientific visualization and data segmentation. In this thesis, three practical tools are presented. Two of these tools are software systems (Insight and IWAL) for different types of processing and interactive visualization of data, the third tool is an efficient algorithm for data segmentation implemented as part of Insight.Insight is a toolkit for the interactive, three-dimensional visualization and processing of large sets of atmospheric data, originally developed as a testing environment for the novel segmentation algorithm. It provides a dynamic system for combining at runtime data from different sources, a variety of different data processing algorithms, and several visualization techniques. Its modular architecture and flexible scripting support led to additional applications of the software, from which two examples are presented: the usage of Insight as a WMS (web map service) server, and the automatic production of a sequence of images for the visualization of cyclone simulations. The core application of Insight is the provision of the novel segmentation algorithm for the efficient detection and tracking of 3D features in large sets of atmospheric data, as well as for the precise localization of the occurring genesis, lysis, merging and splitting events. Data segmentation usually leads to a significant reduction of the size of the considered data. This enables a practical visualization of the data, statistical analyses of the features and their events, and the manual or automatic detection of interesting situations for subsequent detailed investigation. The concepts of the novel algorithm, its technical realization, and several extensions for avoiding under- and over-segmentation are discussed. As example applications, this thesis covers the setup and the results of the segmentation of upper-tropospheric jet streams and cyclones as full 3D objects. Finally, IWAL is presented, which is a web application for providing an easy interactive access to meteorological data visualizations, primarily aimed at students. As a web application, the needs to retrieve all input data sets and to install and handle complex visualization tools on a local machine are avoided. The main challenge in the provision of customizable visualizations to large numbers of simultaneous users was to find an acceptable trade-off between the available visualization options and the performance of the application. Besides the implementational details, benchmarks and the results of a user survey are presented.