Hydrocarbon sensors for oil spill prevention and response, Seward, Alaska, April 8th-10th, 2008: workshop proceedings

During April 8th-10th, 2008, the Aliance for Coastal Technology (ACT) partner institutions, University of Alaska Fairbanks (UAF), Alaska SeaLife Center (ASLC), and the Oil Spill Recovery Institute (OSRI) hosted a workshop entitled: "Hydrocarbon sensors for oil spill prevention and response" in Seward, Alaska. The main focus was to bring together 29 workshop participants-representing workshop managers, scientists, and technology developers - together to discuss current and future hydrocarbon in-situ, laboratory, and remote sensors as they apply to oil spill prevention and response. [PDF contains 28 pages] Hydrocarbons and their derivatives still remain one of the most important energy sources in the world. To effectively manage these energy sources, proper protocol must be implemented to ensure prevention and responses to oil spills, as there are significant economic and environmental costs when oil spills occur. Hydrocarbon sensors provide the means to detect and monitor oil spills before, during, and after they occur. Capitalizing on the properties of oil, developers have designed in-situ, laboratory, and remote sensors that absorb or reflect the electromagnetic energy at different spectral bands. Workshop participants identified current hydrocarbon sensors (in-situ, laboratory, and remote sensors) and their overall performance. To achieve the most comprehensive understanding of oil spills, multiple sensors will be needed to gather oil spill extent, location, movement, thickness, condition, and classification. No single hydrocarbon sensor has the capability to collect all this information. Participants, therefore, suggested the development of means to combine sensor equipment to effectively and rapidly establish a spill response. As the exploration of oil continues at polar latitudes, sensor equipment must be developed to withstand harsh arctic climates, be able to detect oil under ice, and reduce the need for ground teams because ice extent is far too large of an area to cover. Participants also recognized the need for ground teams because ice extent is far too large of an area to cover. Participants also recognized the need for the U.S. to adopt a multi-agency cooperation for oil spill response, as the majority of issues surounding oil spill response focuses not on the hydrocarbon sensors but on an effective contingency plan adopted by all agencies. It is recommended that the U.S. could model contingency planning based on other nations such as Germany and Norway. Workshop participants were asked to make recommendations at the conclusion of the workshop and are summarized below without prioritization: *Outreach materials must be delivered to funding sources and Congressional delegates regarding the importance of oil spill prevention and response and the development of proper sensors to achieve effective response. *Develop protocols for training resource managers as new sensors become available. *Develop or adopt standard instrument specifications and testing protocols to assist manufacturers in further developing new sensor technology. *As oil exploration continues at polar latitudes, more research and development should be allocated to develop a suite of instruments that are applicable to oil detection under ice.

Underwater Passive Acoustic Monitoring for Remote Regions, Hawaii Institute of Marine Biology, Coconut Island, Hawaii, February 7-9, 2007: workshop proceedings

The Alliance for Coastal Technologies (ACT) convened a workshop, sponsored by the Hawaii-Pacific and Alaska Regional Partners, entitled Underwater Passive Acoustic Monitoring for Remote Regions at the Hawaii Institute of Marine Biology from February 7-9, 2007. The workshop was designed to summarize existing passive acoustic technologies and their uses, as well as to make strategic recommendations for future development and collaborative programs that use passive acoustic tools for scientific investigation and resource management. The workshop was attended by 29 people representing three sectors: research scientists, resource managers, and technology developers. The majority of passive acoustic tools are being developed by individual scientists for specific applications and few tools are available commercially. Most scientists are developing hydrophone-based systems to listen for species-specific information on fish or cetaceans; a few scientists are listening for biological indicators of ecosystem health. Resource managers are interested in passive acoustics primarily for vessel detection in remote protected areas and secondarily to obtain biological and ecological information. The military has been monitoring with hydrophones for decades;however, data and signal processing software has not been readily available to the scientific community, and future collaboration is greatly needed. The challenges that impede future development of passive acoustics are surmountable with greater collaboration. Hardware exists and is accessible; the limits are in the software and in the interpretation of sounds and their correlation with ecological events. Collaboration with the military and the private companies it contracts will assist scientists and managers with obtaining and developing software and data analysis tools. Collaborative proposals among scientists to receive larger pools of money for exploratory acoustic science will further develop the ability to correlate noise with ecological activities. The existing technologies and data analysis are adequate to meet resource managers' needs for vessel detection. However, collaboration is needed among resource managers to prepare large-scale programs that include centralized processing in an effort to address the lack of local capacity within management agencies to analyze and interpret the data. Workshop participants suggested that ACT might facilitate such collaborations through its website and by providing recommendations to key agencies and programs, such as DOD, NOAA, and I00s. There is a need to standardize data formats and archive acoustic environmental data at the national and international levels. Specifically, there is a need for local training and primers for public education, as well as by pilot demonstration projects, perhaps in conjunction with National Marine Sanctuaries. Passive acoustic technologies should be implemented immediately to address vessel monitoring needs. Ecological and health monitoring applications should be developed as vessel monitoring programs provide additional data and opportunities for more exploratory research. Passive acoustic monitoring should also be correlated with water quality monitoring to ease integration into long-term monitoring programs, such as the ocean observing systems. [PDF contains 52 pages]

Optical Remote Sensing of Coastal Habitats, Moss Landing, California, 9-11 January, 2006: workshop proceedings

The Alliance for Coastal Technologies (ACT) Workshop on Optical Remote Sensing of Coastal Habitats was convened January 9-11, 2006 at Moss Landing Marine Laboratories in Moss Landing, California, sponsored by the ACT West Coast regional partnership comprised of the Moss Landing Marine Laboratories (MLML) and the Monterey Bay Aquarium Research Institute (MBARI). The "Optical Remote Sensing of Coastal Habitats" (ORS) Workshop completes ACT'S Remote Sensing Technology series by building upon the success of ACT'S West Coast Regional Partner Workshop "Acoustic Remote Sensing Technologies for Coastal Imaging and Resource Assessment" (ACT 04-07). Drs. Paul Bissett of the Florida Environmental Research Institute (FERI) and Scott McClean of Satlantic, Inc. were the ORS workshop co-chairs. Invited participants were selected to provide a uniform representation of the academic researchers, private sector product developers, and existing and potential data product users from the resource management community to enable development of broad consensus opinions on the role of ORS technologies in coastal resource assessment and management. The workshop was organized to examine the current state of multi- and hyper-spectral imaging technologies with the intent to assess the current limits on their routine application for habitat classification and resource monitoring of coastal watersheds, nearshore shallow water environments, and adjacent optically deep waters. Breakout discussions focused on the capabilities, advantages ,and limitations of the different technologies (e.g., spectral & spatial resolution), as well as practical issues related to instrument and platform availability, reliability, hardware, software, and technical skill levels required to exploit the data products generated by these instruments. Specifically, the participants were charged to address the following: (1) Identify the types of ORS data products currently used for coastal resource assessment and how they can assist coastal managers in fulfilling their regulatory and management responsibilities; (2) Identify barriers and challenges to the application of ORS technologies in management and research activities; (3) Recommend a series of community actions to overcome identified barriers and challenges. Plenary presentations by Drs. Curtiss 0. Davis (Oregon State University) and Stephan Lataille (ITRES Research, Ltd.) provided background summaries on the varieties of ORS technologies available, deployment platform options, and tradeoffs for application of ORS data products with specific applications to the assessment of coastal zone water quality and habitat characterization. Dr. Jim Aiken (CASIX) described how multiscale ground-truth measurements were essential for developing robust assessment of modeled biogeochemical interpretations derived from optically based earth observation data sets. While continuing improvements in sensor spectral resolution, signal to noise and dynamic range coupled with sensor-integrated GPS, improved processing algorithms for georectification, and atmospheric correction have made ORS data products invaluable synoptic tools for oceanographic research, their adoption as management tools has lagged. Seth Blitch (Apalachicola National Estuarine Research Reserve) described the obvious needs for, yet substantial challenges hindering the adoption of advanced spectroscopic imaging data products to supplement the current dominance of digital ortho-quad imagery by the resource management community, especially when they impinge on regulatory issues. (pdf contains 32 pages)

Contributions to the analysis and segmentation of remote sensing hyperspectral images

142 p.

Embryonic development in Clarias gariepinus under laboratory conditions

The embryonic development in Clarias gariepinus was studied under laboratory conditions. The developmental stages of eggs starting from first cleavage were examined microscopically. Photomicroscope was used to take important stages of segmentation, blastulation, differentiation of embryo and hatching. The films of the photograph were developed and printed for each stage produced. The accurate timing and detailed description of each stage was done. The results show that the blastodisc (Polar cap) appeared about 35 minutes after fertilization and the first cleavage dividing the blastodisc into two blastomeres occurs 15 minutes after polar cap formation. Details of the developmental stages of embryos and the timing from one stage to the other were described. The larva shook off the shell and emerged completely from the egg case about 22 hours after fertilization at a water temperature of 25.1 degree C. The accurate determination of the time of initiation of first mitosis is of great importance in fish culture and breeding especially in the production of tetraploids

Resource management of dynamic coastal environments using synoptic measures from remote sensing

In addition to providing vital ecological services, coastal areas of North Carolina provide prized areas for habitation, recreation, and commercial fisheries. However, from a management perspective, the coasts of North Carolina are highly variable and complex. In-water constituents such as nutrients, suspended sediments, and chlorophyll a concentration can vary significantly over a broad spectrum of time and space scales. Rapid growth and land-use change continue to exert pressure on coastal lands. Coastal environments are also very vulnerable to short-term (e.g., hurricanes) and long-term (e.g., sea-level rise) natural changes that can result in significant loss of life, economic loss, or changes in coastal ecosystem functioning. Hence, the dynamic nature, effects of human-induced change over time, and vulnerability of coastal areas make it difficult to effectively monitor and manage these important state and national resources using traditional data collection technologies such as discrete monitoring stations and field surveys. In general, these approaches provide only a sparse network of data over limited time and space scales and generally are expensive and labor-intensive. Products derived from spectral images obtained by remote sensing instruments provide a unique vantage point from which to examine the dynamic nature of coastal environments. A primary advantage of remote sensing is that the altitude of observation provides a large-scale synoptic view relative to traditional field measurements. Equally important, the use of remote sensing for a broad range of research and environmental applications is now common due to major advances in data availability, data transfer, and computer technologies. To facilitate the widespread use of remote sensing products in North Carolina, the UNC Coastal Studies Institute (UNC-CSI) is developing the capability to acquire, process, and analyze remotely sensed data from several remote sensing instruments. In particular, UNC-CSI is developing regional remote sensing algorithms to examine the mobilization, transport, transformation, and fate of materials between coupled terrestrial and coastal ocean systems. To illustrate this work, we present the basic principles of remote sensing of coastal waters in the context of deriving information that supports efficient and effective management of coastal resources. (PDF contains 4 pages)

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.

Wind-driven desertification: process modeling, remote monitoring, and forecasting

Arid and semiarid landscapes comprise nearly a third of the Earth's total land surface. These areas are coming under increasing land use pressures. Despite their low productivity these lands are not barren. Rather, they consist of fragile ecosystems vulnerable to anthropogenic disturbance.

The purpose of this thesis is threefold: (I) to develop and test a process model of wind-driven desertification, (II) to evaluate next-generation process-relevant remote monitoring strategies for use in arid and semiarid regions, and (III) to identify elements for effective management of the world's drylands.

In developing the process model of wind-driven desertification in arid and semiarid lands, field, remote sensing, and modeling observations from a degraded Mojave Desert shrubland are used. This model focuses on aeolian removal and transport of dust, sand, and litter as the primary mechanisms of degradation: killing plants by burial and abrasion, interrupting natural processes of nutrient accumulation, and allowing the loss of soil resources by abiotic transport. This model is tested in field sampling experiments at two sites and is extended by Fourier Transform and geostatistical analysis of high-resolution imagery from one site.

Next, the use of hyperspectral remote sensing data is evaluated as a substantive input to dryland remote monitoring strategies. In particular, the efficacy of spectral mixture analysis (SMA) in discriminating vegetation and soil types and detennining vegetation cover is investigated. The results indicate that hyperspectral data may be less useful than often thought in determining vegetation parameters. Its usefulness in determining soil parameters, however, may be leveraged by developing simple multispectral classification tools that can be used to monitor desertification.

Finally, the elements required for effective monitoring and management of arid and semiarid lands are discussed. Several large-scale multi-site field experiments are proposed to clarify the role of wind as a landscape and degradation process in dry lands. The role of remote sensing in monitoring the world's drylands is discussed in terms of optimal remote sensing platform characteristics and surface phenomena which may be monitored in order to identify areas at risk of desertification. A desertification indicator is proposed that unifies consideration of environmental and human variables.

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.

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

[no abstract]