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Most taste-and-odor problems in the United States are caused by algal blooms in rivers and reservoirs. In the past, most of the attention has been focused on the formation of geosmin and MIB by blue-green algae (cyanobacteria), which cause earthy and musty odors, respectively. Little work has been performed, however, on equally obnoxious odors caused by other golden-brown and yellow-brown algae which are responsible for fishy, grassy, floral, and melon odors. Additionally, the production of odorous compounds can occur upon oxidation of a nonodorous parent compound. The objective of this research was to determine the effect of three oxidants - chlorine, potassium permanganate, and chlorine dioxide - on solutions of pure odorous as well as nonodorous compounds and algal extracts containing a mixture of odor-related compounds. Oxidant dosages used were in the ranges expected during water treatment. Rashash (1994) identified several odor-causing compounds in pure cultures of golden-brown, yellow-brown, green, and blue-green algae. The compounds selected for oxidation during this study were isolated by Rashash (1994) and are as follows: isovaleric acid (rancid, dirty socks), β-cyclocitral (tobacco, grape), phenethyl alcohol (roses), myristic acid (odorless), palmitic acid (odorless), linoleic acid (odorless), and linolenic acid (watermelon). All seven compounds were oxidized and evaluated by a trained flavor panel for sensory analysis. Because the three oxidants used in this study produced substantial changes in the odors of linoleic acid and linolenic acid, test solutions buffered to a pH of 7 of linoleic acid and linolenic acid were further evaluated by Flavor Profile Analysis (FPA) for sensory determination and gas chromatography/mass spectroscopy (GC/MS) for quantitative measurement of odorous compounds. Volatile compounds produced by Synura petersenii (fishy/cucumber) were also analyzed and evaluated. When linoleic acid (odorless) was treated with potassium permanganate (0.25 mg/L, 1.0 mg/L, and 1.5 mg/L) and chlorine dioxide (1.0 mg/L and 2.0 mg/L), a grassy odor was produced at an FPA intensity of 2-4 (weak). The compound causing this odor was confidently identified from GC/MS analysis as n-hexanal. The compound 2,4-decadienal, which exhibits a frying odor, was also identified in oxidized samples and could contribute to off-odors. Chlorine dioxide and potassium permanganate at the same doses were also effective in eliminating watermelon odors in linolenic samples. Flavor Profile Analysis of samples treated with chlorine was inconclusive since chlorine and acetone, which was used as an organic solvent, produce an alcohol odor at an FPA intensity of approximately 2 (weak) which masked other odors present. Flavor Profile Analysis of oxidized Synura extracts indicated that the fishy odor was destroyed and cucumber or grassy odors were unmasked. Potassium permanganate at a concentration of 0.25 mg/L was effective in eliminating all odors in Synura culture samples. Chlorine and chlorine dioxide at concentrations of 2.0 mg/L and 3.0 mg/L, respectively, eliminated the fishy odor in Synura samples. In both cases, however, vegetation or grassy odors were detected at an FPA intensity of less than 2 (very weak). / Master of Science

The purpose of this investigation is to attempt to relate the distribution and periodicity of the plankton to the variations in the biological, chemical, and physical factors.

This dissertation consists of three separate research projects. Each paper uses a different applied econometric technique to investigate problems related to air quality economics. The first chapter is a general introduction to all three studies. The second chapter explores adopting an environmentally-friendly public transportation system in Europe. The Bayesian econometric methods show that willingness to pay for a new public transportation system is primarily driven by improvements to public goods, such as air quality and greenhouse gas emission reduction. The third chapter uses the red tide-related stated experience and satellite imagery of chlorophyll-a concentration as well as field data of respiratory irritation. This chapter illustrates that ancillary scientific information can be efficiently combined with choice experimental data. The fourth chapter uses panel fixed-effect models to investigate the short-term effect of air pollution on students' cognitive performance in China. It is shown that PM2.5 has a significantly negative impact on students' exam performance. / Doctor of Philosophy / This dissertation consists of three separate research projects. The first chapter is a general introduction to all three chapters. The second chapter assesses residents' support for environmentally-friendly public transportation (EFPT) upgrades across Europe. We develop a novel Bayesian logit model to investigate residents' willingness to pay for local EFPT upgrades. We find evidence that WTP is primarily driven by expected improvements to public goods, such as air quality and greenhouse gas abatement, as opposed to private ridership benefits. WTP distributions are strongly positive in all nations suggesting implicit public support for EFPT in Europe. The third chapter presents a unique opportunity to validate stated experiences by Florida Gulf coast residents with red tide-related air toxins with satellite imagery of chlorophyll-a concentration, as well as field data on respiratory irritation at local beaches. We find that respondents are more likely to choose our proposed new harmful algal blooms forecast system when the chlorophyll-a concentration or respiratory irritation is higher at nearby coastal locations. Moreover, we illustrate that this ancillary scientific information can be efficiently combined with choice experimental data and consider this research a first step in a broader effort to directly link scientific data on environmental conditions with nonmarket economic outcomes. The fourth chapter investigates short-term exposure of air pollution on students' cognitive performance in a high-stakes exam: China's College English Test (CET). We use student fixed effects in the panel-data model to estimate the effect of air pollution on students' test scores. Our findings indicate a statistically significant negative effect of PM2.5 on exam performance and also show PM2.5 is equally harmful to listening and reading section, and maybe even more for writing section. We also find that short-term exposure causes negative cognitive effects, suggesting that temporary preventative measures could be effective in avoiding the negative effects of PM2.5.

Lakes and oceans are threatened by harmful algal blooms (HABs), caused mostly by toxic cyanobacteria. When people or animals drink the toxic water, it can be damaging to their health, potentially leading to hospitalization or even death. In some cases, these toxins are not just limited to the water, but can become airborne through wave breaking, bubble bursting, and spume droplet formation. New information is needed regarding the transport and fate of HAB-associated aerosols. The overall goal of this research was to monitor particle concentrations and measure meteorological conditions near HAB sites to determine the conditions that may lead to increased exposure to HAB cells and toxins in the atmosphere. By creating predictions of which conditions and locations will be experiencing higher aerosol levels at any given time, models could be used to inform the public and policy makers to ensure that appropriate responses and safety measures can be taken. The research also includes experiments to study plumes of colored smoke, as a proxy for the transport of biological particles such as HAB cells, pollen, and pathogens. The first objective of this research was to explore associations between measured weather conditions and particle concentrations measured above active HABs and HAB sites using drone-based sensor packages. The second objective was to monitor wind and particle concentrations near freshwater and marine HABs using ground-based sensor packages. The third objective was to model HAB aerosol behavior at a beach level to predict respiratory irritation. The fourth objective was to use aerial and ground-based sensors and images of colored smoke to predict particle concentrations at different distances and intensity levels downwind from the source(s). / Doctor of Philosophy / Certain environmental conditions in lakes and oceans can favor unhealthy amounts of algal growth. Overgrowth can lead to harmful algal blooms (HABs). This occurs when algae produce toxins that make the water unsafe for humans and animals to drink. Sometimes these toxins don't stay in the water and can become toxic airborne particles. We need more information to understand what happens to create and transport these airborne toxins produced by HABs. This research aims to monitor particle concentrations and weather to find what conditions lead to more aerosolized toxins. Accurate predictions of high levels of HAB toxins in the air could be used to alert the public. This work utilized colored smoke released outdoors as a visual indicator of particle movement in the air. The specific objectives of this research were to (1) find associations between weather and particle concentrations at lake HAB sites using drone-mounted samplers at a height above 30 feet from the ground, (2) find associations between weather and particle concentrations at lake and ocean HAB sites using samplers at a height of 5 feet from the ground, (3) predict human throat irritation levels from airborne toxins at the beach level, and (4) use a drone sensor, a ground sensor, and simultaneous video footage of a controlled smoke release to visually track airborne particles.

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