Investigations of secondary organic aerosol formation in laboratory chambers

Secondary organic aerosol (SOA) is produced in the atmosphere by oxidation of volatile organic compounds. Laboratory chambers are used understand the formation mechanisms and evolution of SOA formed under controlled conditions. This thesis presents studies of SOA formed from anthropogenic and biogenic precursors and discusses the effects of chamber walls on suspended vapors and particles.

During a chamber experiment, suspended vapors and particles can interact with the chamber walls. Particle wall loss is relatively well-understood, but vapor wall losses have received little study. Vapor wall loss of 2,3-epoxy-1,4-butanediol (BEPOX) and glyoxal was identified, quantified, and found to depend on chamber age and relative humidity.

Particles reside in the atmosphere for a week or more and can evolve chemically during that time period, a process termed aging. Simulating aging in laboratory chambers has proven to be challenging. A protocol was developed to extend the duration of a chamber experiment to 36 h of oxidation and was used to evaluate aging of SOA produced from m-xylene. Total SOA mass concentration increased and then decreased with increasing photooxidation suggesting a transition from functionalization to fragmentation chemistry driven by photochemical processes. SOA oxidation, measured as the bulk particle elemental oxygen-to-carbon ratio and fraction of organic mass at m/z 44, increased continuously starting after 5 h of photooxidation.

The physical state and chemical composition of an organic aerosol affect the mixing of aerosol components and its interactions with condensing species. A laboratory chamber protocol was developed to evaluate the mixing of SOA produced sequentially from two different sources by heating the chamber to induce particle evaporation. Using this protocol, SOA produced from toluene was found to be less volatile than that produced from a-pinene. When the two types of SOA were formed sequentially, the evaporation behavior most closely represented that of SOA from the second parent hydrocarbon, suggesting that the structure of the mixed SOA particles resembles a core of SOA from the first precursor coated by a layer of SOA from the second precursor, indicative of limiting mixing.

Efficient methods for empirical tests of behavioral economics theories in laboratory and field experiments

In the quest for a descriptive theory of decision-making, the rational actor model in economics imposes rather unrealistic expectations and abilities on human decision makers. The further we move from idealized scenarios, such as perfectly competitive markets, and ambitiously extend the reach of the theory to describe everyday decision making situations, the less sense these assumptions make. Behavioural economics has instead proposed models based on assumptions that are more psychologically realistic, with the aim of gaining more precision and descriptive power. Increased psychological realism, however, comes at the cost of a greater number of parameters and model complexity. Now there are a plethora of models, based on different assumptions, applicable in differing contextual settings, and selecting the right model to use tends to be an ad-hoc process. In this thesis, we develop optimal experimental design methods and evaluate different behavioral theories against evidence from lab and field experiments.

We look at evidence from controlled laboratory experiments. Subjects are presented with choices between monetary gambles or lotteries. Different decision-making theories evaluate the choices differently and would make distinct predictions about the subjects' choices. Theories whose predictions are inconsistent with the actual choices can be systematically eliminated. Behavioural theories can have multiple parameters requiring complex experimental designs with a very large number of possible choice tests. This imposes computational and economic constraints on using classical experimental design methods. We develop a methodology of adaptive tests: Bayesian Rapid Optimal Adaptive Designs (BROAD) that sequentially chooses the "most informative" test at each stage, and based on the response updates its posterior beliefs over the theories, which informs the next most informative test to run. BROAD utilizes the Equivalent Class Edge Cutting (EC²) criteria to select tests. We prove that the EC² criteria is adaptively submodular, which allows us to prove theoretical guarantees against the Bayes-optimal testing sequence even in the presence of noisy responses. In simulated ground-truth experiments, we find that the EC² criteria recovers the true hypotheses with significantly fewer tests than more widely used criteria such as Information Gain and Generalized Binary Search. We show, theoretically as well as experimentally, that surprisingly these popular criteria can perform poorly in the presence of noise, or subject errors. Furthermore, we use the adaptive submodular property of EC² to implement an accelerated greedy version of BROAD which leads to orders of magnitude speedup over other methods.

We use BROAD to perform two experiments. First, we compare the main classes of theories for decision-making under risk, namely: expected value, prospect theory, constant relative risk aversion (CRRA) and moments models. Subjects are given an initial endowment, and sequentially presented choices between two lotteries, with the possibility of losses. The lotteries are selected using BROAD, and 57 subjects from Caltech and UCLA are incentivized by randomly realizing one of the lotteries chosen. Aggregate posterior probabilities over the theories show limited evidence in favour of CRRA and moments' models. Classifying the subjects into types showed that most subjects are described by prospect theory, followed by expected value. Adaptive experimental design raises the possibility that subjects could engage in strategic manipulation, i.e. subjects could mask their true preferences and choose differently in order to obtain more favourable tests in later rounds thereby increasing their payoffs. We pay close attention to this problem; strategic manipulation is ruled out since it is infeasible in practice, and also since we do not find any signatures of it in our data.

In the second experiment, we compare the main theories of time preference: exponential discounting, hyperbolic discounting, "present bias" models: quasi-hyperbolic (α, β) discounting and fixed cost discounting, and generalized-hyperbolic discounting. 40 subjects from UCLA were given choices between 2 options: a smaller but more immediate payoff versus a larger but later payoff. We found very limited evidence for present bias models and hyperbolic discounting, and most subjects were classified as generalized hyperbolic discounting types, followed by exponential discounting.

In these models the passage of time is linear. We instead consider a psychological model where the perception of time is subjective. We prove that when the biological (subjective) time is positively dependent, it gives rise to hyperbolic discounting and temporal choice inconsistency.

We also test the predictions of behavioral theories in the "wild". We pay attention to prospect theory, which emerged as the dominant theory in our lab experiments of risky choice. Loss aversion and reference dependence predicts that consumers will behave in a uniquely distinct way than the standard rational model predicts. Specifically, loss aversion predicts that when an item is being offered at a discount, the demand for it will be greater than that explained by its price elasticity. Even more importantly, when the item is no longer discounted, demand for its close substitute would increase excessively. We tested this prediction using a discrete choice model with loss-averse utility function on data from a large eCommerce retailer. Not only did we identify loss aversion, but we also found that the effect decreased with consumers' experience. We outline the policy implications that consumer loss aversion entails, and strategies for competitive pricing.

In future work, BROAD can be widely applicable for testing different behavioural models, e.g. in social preference and game theory, and in different contextual settings. Additional measurements beyond choice data, including biological measurements such as skin conductance, can be used to more rapidly eliminate hypothesis and speed up model comparison. Discrete choice models also provide a framework for testing behavioural models with field data, and encourage combined lab-field experiments.

Field and Laboratory Studies of Atmospheric Organic Aerosol

This thesis is the culmination of field and laboratory studies aimed at assessing processes that affect the composition and distribution of atmospheric organic aerosol. An emphasis is placed on measurements conducted using compact and high-resolution Aerodyne Aerosol Mass Spectrometers (AMS). The first three chapters summarize results from aircraft campaigns designed to evaluate anthropogenic and biogenic impacts on marine aerosol and clouds off the coast of California. Subsequent chapters describe laboratory studies intended to evaluate gas and particle-phase mechanisms of organic aerosol oxidation.

The 2013 Nucleation in California Experiment (NiCE) was a campaign designed to study environments impacted by nucleated and/or freshly formed aerosol particles. Terrestrial biogenic aerosol with > 85% organic mass was observed to reside in the free troposphere above marine stratocumulus. This biogenic organic aerosol (BOA) originated from the Northwestern United States and was transported to the marine atmosphere during periodic cloud-clearing events. Spectra recorded by a cloud condensation nuclei counter demonstrated that BOA is CCN active. BOA enhancements at latitudes north of San Francisco, CA coincided with enhanced cloud water concentrations of organic species such as acetate and formate.

Airborne measurements conducted during the 2011 Eastern Pacific Emitted Aerosol Cloud Experiment (E-PEACE) were aimed at evaluating the contribution of ship emissions to the properties of marine aerosol and clouds off the coast of central California. In one study, analysis of organic aerosol mass spectra during periods of enhanced shipping activity yielded unique tracers indicative of cloud-processed ship emissions (m/z 42 and 99). The variation of their organic fraction (f₄₂ and f₉₉) was found to coincide with periods of heavy (f₄₂ > 0.15; f₉₉ > 0.04), moderate (0.05 < f₄₂ < 0.15; 0.01 < f₉₉ < 0.04), and negligible (f₄₂ < 0.05; f₉₉ < 0.01) ship influence. Application of these conditions to all measurements conducted during E-PEACE demonstrated that a large fraction of cloud droplet (72%) and dry aerosol mass (12%) sampled in the California coastal study region was heavily or moderately influenced by ship emissions. Another study investigated the chemical and physical evolution of a controlled organic plume emitted from the R/V Point Sur. Under sunny conditions, nucleated particles composed of oxidized organic compounds contributed nearly an order of magnitude more cloud condensation nuclei (CCN) than less oxidized particles formed under cloudy conditions. The processing time necessary for particles to become CCN active was short ( < 1 hr) compared to the time needed for particles to become hygroscopic at sub-saturated humidity ( > 4 hr).

Laboratory chamber experiments were also conducted to evaluate particle-phase processes influencing aerosol phase and composition. In one study, ammonium sulfate seed was coated with a layer of secondary organic aerosol (SOA) from toluene oxidation followed by a layer of SOA from α-pinene oxidation. The system exhibited different evaporative properties than ammonium sulfate seed initially coated with α-pinene SOA followed by a layer of toluene SOA. This behavior is consistent with a shell-and-core model and suggests limited mixing among different SOA types. Another study investigated the reactive uptake of isoprene epoxy diols (IEPOX) onto non-acidified aerosol. It was demonstrated that particle acidity has limited influence on organic aerosol formation onto ammonium sulfate seed, and that the chemical system is limited by the availability of nucleophiles such as sulfate.

Flow tube experiments were conducted to examine the role of iron in the reactive uptake and chemical oxidation of glycolaldehyde. Aerosol particles doped with iron and hydrogen peroxide were mixed with gas-phase glycolaldehyde and photochemically aged in a custom-built flow reactor. Compared to particles free of iron, iron-doped aerosols significantly enhanced the oxygen to carbon (O/C) ratio of accumulated organic mass. The primary oxidation mechanism is suggested to be a combination of Fenton and photo-Fenton reactions which enhance particle-phase OH radical concentrations.

On-chip integrated label-free optical biosensing

This thesis investigates the design and implementation of a label-free optical biosensing system utilizing a robust on-chip integrated platform. The goal has been to transition optical micro-resonator based label-free biosensing from a laborious and delicate laboratory demonstration to a tool for the analytical life scientist. This has been pursued along four avenues: (1) the design and fabrication of high-$Q$ integrated planar microdisk optical resonators in silicon nitride on silica, (2) the demonstration of a high speed optoelectronic swept frequency laser source, (3) the development and integration of a microfluidic analyte delivery system, and (4) the introduction of a novel differential measurement technique for the reduction of environmental noise.

The optical part of this system combines the results of two major recent developments in the field of optical and laser physics: the high-$Q$ optical resonator and the phase-locked electronically controlled swept-frequency semiconductor laser. The laser operates at a wavelength relevant for aqueous sensing, and replaces expensive and fragile mechanically-tuned laser sources whose frequency sweeps have limited speed, accuracy and reliability. The high-$Q$ optical resonator is part of a monolithic unit with an integrated optical waveguide, and is fabricated using standard semiconductor lithography methods. Monolithic integration makes the system significantly more robust and flexible compared to current, fragile embodiments that rely on the precarious coupling of fragile optical fibers to resonators. The silicon nitride on silica material system allows for future manifestations at shorter wavelengths. The sensor also includes an integrated microfluidic flow cell for precise and low volume delivery of analytes to the resonator surface. We demonstrate the refractive index sensing action of the system as well as the specific and nonspecific adsorption of proteins onto the resonator surface with high sensitivity. Measurement challenges due to environmental noise that hamper system performance are discussed and a differential sensing measurement is proposed, implemented, and demonstrated resulting in the restoration of a high performance sensing measurement.

The instrument developed in this work represents an adaptable and cost-effective platform capable of various sensitive, label-free measurements relevant to the study of biophysics, biomolecular interactions, cell signaling, and a wide range of other life science fields. Further development is necessary for it to be capable of binding assays, or thermodynamic and kinetics measurements; however, this work has laid the foundation for the demonstration of these applications.

Probabilistic robust control : theory and applications

In this work, the development of a probabilistic approach to robust control is motivated by structural control applications in civil engineering. Often in civil structural applications, a system's performance is specified in terms of its reliability. In addition, the model and input uncertainty for the system may be described most appropriately using probabilistic or "soft" bounds on the model and input sets. The probabilistic robust control methodology contrasts with existing H∞/μ robust control methodologies that do not use probability information for the model and input uncertainty sets, yielding only the guaranteed (i.e., "worst-case") system performance, and no information about the system's probable performance which would be of interest to civil engineers.

The design objective for the probabilistic robust controller is to maximize the reliability of the uncertain structure/controller system for a probabilistically-described uncertain excitation. The robust performance is computed for a set of possible models by weighting the conditional performance probability for a particular model by the probability of that model, then integrating over the set of possible models. This integration is accomplished efficiently using an asymptotic approximation. The probable performance can be optimized numerically over the class of allowable controllers to find the optimal controller. Also, if structural response data becomes available from a controlled structure, its probable performance can easily be updated using Bayes's Theorem to update the probability distribution over the set of possible models. An updated optimal controller can then be produced, if desired, by following the original procedure. Thus, the probabilistic framework integrates system identification and robust control in a natural manner.

The probabilistic robust control methodology is applied to two systems in this thesis. The first is a high-fidelity computer model of a benchmark structural control laboratory experiment. For this application, uncertainty in the input model only is considered. The probabilistic control design minimizes the failure probability of the benchmark system while remaining robust with respect to the input model uncertainty. The performance of an optimal low-order controller compares favorably with higher-order controllers for the same benchmark system which are based on other approaches. The second application is to the Caltech Flexible Structure, which is a light-weight aluminum truss structure actuated by three voice coil actuators. A controller is designed to minimize the failure probability for a nominal model of this system. Furthermore, the method for updating the model-based performance calculation given new response data from the system is illustrated.

A. An investigation of the relation between the tensile strength and (Brinell) hardness of non-ferrous alloys. B. A design of a fatigue testing machine for a college laboratory

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Secondary Organic Aerosol Composition Studies Using Mass Spectrometry

Trace volatile organic compounds emitted by biogenic and anthropogenic sources into the atmosphere can undergo extensive photooxidation to form species with lower volatility. By equilibrium partitioning or reactive uptake, these compounds can nucleate into new aerosol particles or deposit onto already-existing particles to form secondary organic aerosol (SOA). SOA and other atmospheric particulate matter have measurable effects on global climate and public health, making understanding SOA formation a needed field of scientific inquiry. SOA formation can be done in a laboratory setting, using an environmental chamber; under these controlled conditions it is possible to generate SOA from a single parent compound and study the chemical composition of the gas and particle phases. By studying the SOA composition, it is possible to gain understanding of the chemical reactions that occur in the gas phase and particle phase, and identify potential heterogeneous processes that occur at the surface of SOA particles. In this thesis, mass spectrometric methods are used to identify qualitatively and qualitatively the chemical components of SOA derived from the photooxidation of important anthropogenic volatile organic compounds that are associated with gasoline and diesel fuels and industrial activity (C12 alkanes, toluene, and o-, m-, and p-cresols). The conditions under which SOA was generated in each system were varied to explore the effect of NO_x and inorganic seed composition on SOA chemical composition. The structure of the parent alkane was varied to investigate the effect on the functionalization and fragmentation of the resulting oxidation products. Relative humidity was varied in the alkane system as well to measure the effect of increased particle-phase water on condensed-phase reactions. In all systems, oligomeric species, resulting potentially from particle-phase and heterogeneous processes, were identified. Imines produced by reactions between (NH₄)₂SO₄ seed and carbonyl compounds were identified in all systems. Multigenerational photochemistry producing low- and extremely low-volatility organic compounds (LVOC and ELVOC) was reflected strongly in the particle-phase composition as well.

Investigation of Fundamental Processes Governing Secondary Organic Aerosol Formation in Laboratory Chambers

Our understanding of the processes and mechanisms by which secondary organic aerosol (SOA) is formed is derived from laboratory chamber studies. In the atmosphere, SOA formation is primarily driven by progressive photooxidation of SOA precursors, coupled with their gas-particle partitioning. In the chamber environment, SOA-forming vapors undergo multiple chemical and physical processes that involve production and removal via gas-phase reactions; partitioning onto suspended particles vs. particles deposited on the chamber wall; and direct deposition on the chamber wall. The main focus of this dissertation is to characterize the interactions of organic vapors with suspended particles and the chamber wall and explore how these intertwined processes in laboratory chambers govern SOA formation and evolution.

A Functional Group Oxidation Model (FGOM) that represents SOA formation and evolution in terms of the competition between functionalization and fragmentation, the extent of oxygen atom addition, and the change of volatility, is developed. The FGOM contains a set of parameters that are to be determined by fitting of the model to laboratory chamber data. The sensitivity of the model prediction to variation of the adjustable parameters allows one to assess the relative importance of various pathways involved in SOA formation.

A critical aspect of the environmental chamber is the presence of the wall, which can induce deposition of SOA-forming vapors and promote heterogeneous reactions. An experimental protocol and model framework are first developed to constrain the vapor-wall interactions. By optimal fitting the model predictions to the observed wall-induced decay profiles of 25 oxidized organic compounds, the dominant parameter governing the extent of wall deposition of a compound is identified, i.e., wall accommodation coefficient. By correlating this parameter with the molecular properties of a compound via its volatility, the wall-induced deposition rate of an organic compound can be predicted based on its carbon and oxygen numbers in the molecule.

Heterogeneous transformation of δ-hydroxycarbonyl, a major first-generation product from long-chain alkane photochemistry, is observed on the surface of particles and walls. The uniqueness of this reaction scheme is the production of substituted dihydrofuran, which is highly reactive towards ozone, OH, and NO3, thereby opening a reaction pathway that is not usually accessible to alkanes. A spectrum of highly-oxygenated products with carboxylic acid, ester, and ether functional groups is produced from the substituted dihydrofuran chemistry, thereby affecting the average oxidation state of the alkane-derived SOA.

The vapor wall loss correction is applied to several chamber-derived SOA systems generated from both anthropogenic and biogenic sources. Experimental and modeling approaches are employed to constrain the partitioning behavior of SOA-forming vapors onto suspended particles vs. chamber walls. It is demonstrated that deposition of SOA-forming vapors to the chamber wall during photooxidation experiments can lead to substantial and systematic underestimation of SOA. Therefore, it is likely that a lack of proper accounting for vapor wall losses that suppress chamber-derived SOA yields contribute substantially to the underprediction of ambient SOA concentrations in atmospheric models.

Plasma loop and strapping field dynamics: reproducing solar eruptions in the laboratory

Coronal mass ejections (CMEs) are dramatic eruptions of large, plasma structures from the Sun. These eruptions are important because they can harm astronauts, damage electrical infrastructure, and cause auroras. A mysterious feature of these eruptions is that plasma-filled solar flux tubes first evolve slowly, but then suddenly erupt. One model, torus instability, predicts an explosive-like transition from slow expansion to fast acceleration, if the spatial decay of the ambient magnetic field exceeds a threshold.

We create arched, plasma filled, magnetic flux ropes similar to CMEs. Small, independently-powered auxiliary coils placed inside the vacuum chamber produce magnetic fields above the decay threshold that are strong enough to act on the plasma. When the strapping field is not too strong and not too weak, expansion force build up while the flux rope is in the strapping field region. When the flux rope moves to a critical height, the plasma accelerates quickly, corresponding to the observed slow-rise to fast-acceleration of most solar eruptions. This behavior is in agreement with the predictions of torus instability.

Historically, eruptions have been separated into gradual CMEs and impulsive CMEs, depending on the acceleration profile. Recent numerical studies question this separation. One study varies the strapping field profile to produce gradual eruptions and impulsive eruptions, while another study varies the temporal profile of the voltage applied to the flux tube footpoints to produce the two eruption types. Our experiment reproduced these different eruptions by changing the strapping field magnitude, and the temporal profile of the current trace. This suggests that the same physics underlies both types of CME and that the separation between impulsive and gradual classes of eruption is artificial.

Longitudinal dispersion in laboratory and natural streams

This study concerns the longitudinal dispersion of fluid particles which are initially distributed uninformly over one cross section of a uniform, steady, turbulent open channel flow. The primary focus is on developing a method to predict the rate of dispersion in a natural stream.

Taylor's method of determining a dispersion coefficient, previously applied to flow in pipes and two-dimensional open channels, is extended to a class of three-dimensional flows which have large width-to-depth ratios, and in which the velocity varies continuously with lateral cross-sectional position. Most natural streams are included. The dispersion coefficient for a natural stream may be predicted from measurements of the channel cross-sectional geometry, the cross-sectional distribution of velocity, and the overall channel shear velocity. Tracer experiments are not required.

Large values of the dimensionless dispersion coefficient D/rU* are explained by lateral variations in downstream velocity. In effect, the characteristic length of the cross section is shown to be proportional to the width, rather than the hydraulic radius. The dimensionless dispersion coefficient depends approximately on the square of the width to depth ratio.

A numerical program is given which is capable of generating the entire dispersion pattern downstream from an instantaneous point or plane source of pollutant. The program is verified by the theory for two-dimensional flow, and gives results in good agreement with laboratory and field experiments.

Both laboratory and field experiments are described. Twenty-one laboratory experiments were conducted: thirteen in two-dimensional flows, over both smooth and roughened bottoms; and eight in three-dimensional flows, formed by adding extreme side roughness to produce lateral velocity variations. Four field experiments were conducted in the Green-Duwamish River, Washington.

Both laboratory and flume experiments prove that in three-dimensional flow the dominant mechanism for dispersion is lateral velocity variation. For instance, in one laboratory experiment the dimensionless dispersion coefficient D/rU* (where r is the hydraulic radius and U* the shear velocity) was increased by a factory of ten by roughening the channel banks. In three-dimensional laboratory flow, D/rU* varied from 190 to 640, a typical range for natural streams. For each experiment, the measured dispersion coefficient agreed with that predicted by the extension of Taylor's analysis within a maximum error of 15%. For the Green-Duwamish River, the average experimentally measured dispersion coefficient was within 5% of the prediction.

Aerodynamics of vertical-axis wind turbines in full-scale and laboratory-scale experiments

Within a wind farm, multiple turbine wakes can interact and have a substantial effect on the overall power production. This makes an understanding of the wake recovery process critically important to optimizing wind farm efficiency. Vertical-axis wind turbines (VAWTs) exhibit features that are amenable to dramatically improving this efficiency. However, the physics of the flow around VAWTs is not well understood, especially as it pertains to wake interactions, and it is the goal of this thesis to partially fill this void. This objective is approached from two broadly different perspectives: a low-order view of wind farm aerodynamics, and a detailed experimental analysis of the VAWT wake.

One of the contributions of this thesis is the development of a semi-empirical model of wind farm aerodynamics, known as the LRB model, that is able to predict turbine array configurations to leading order accuracy. Another contribution is the characterization of the VAWT wake as a function of turbine solidity. It was found that three distinct regions of flow exist in the VAWT wake: (1) the near wake, where periodic blade shedding of vorticity dominates; (2) a transition region, where growth of a shear-layer instability occurs; (3) the far wake, where bluff-body oscillations dominate. The wake transition can be predicted using a new parameter, the dynamic solidity, which establishes a quantitative connection between the wake of a VAWT and that of a circular cylinder. The results provide insight into the mechanism of the VAWT wake recovery and the potential means to control it.