2 resultados para STRUCTURAL FEATURES
em Duke University
Resumo:
Human activities represent a significant burden on the global water cycle, with large and increasing demands placed on limited water resources by manufacturing, energy production and domestic water use. In addition to changing the quantity of available water resources, human activities lead to changes in water quality by introducing a large and often poorly-characterized array of chemical pollutants, which may negatively impact biodiversity in aquatic ecosystems, leading to impairment of valuable ecosystem functions and services. Domestic and industrial wastewaters represent a significant source of pollution to the aquatic environment due to inadequate or incomplete removal of chemicals introduced into waters by human activities. Currently, incomplete chemical characterization of treated wastewaters limits comprehensive risk assessment of this ubiquitous impact to water. In particular, a significant fraction of the organic chemical composition of treated industrial and domestic wastewaters remains uncharacterized at the molecular level. Efforts aimed at reducing the impacts of water pollution on aquatic ecosystems critically require knowledge of the composition of wastewaters to develop interventions capable of protecting our precious natural water resources.
The goal of this dissertation was to develop a robust, extensible and high-throughput framework for the comprehensive characterization of organic micropollutants in wastewaters by high-resolution accurate-mass mass spectrometry. High-resolution mass spectrometry provides the most powerful analytical technique available for assessing the occurrence and fate of organic pollutants in the water cycle. However, significant limitations in data processing, analysis and interpretation have limited this technique in achieving comprehensive characterization of organic pollutants occurring in natural and built environments. My work aimed to address these challenges by development of automated workflows for the structural characterization of organic pollutants in wastewater and wastewater impacted environments by high-resolution mass spectrometry, and to apply these methods in combination with novel data handling routines to conduct detailed fate studies of wastewater-derived organic micropollutants in the aquatic environment.
In Chapter 2, chemoinformatic tools were implemented along with novel non-targeted mass spectrometric analytical methods to characterize, map, and explore an environmentally-relevant “chemical space” in municipal wastewater. This was accomplished by characterizing the molecular composition of known wastewater-derived organic pollutants and substances that are prioritized as potential wastewater contaminants, using these databases to evaluate the pollutant-likeness of structures postulated for unknown organic compounds that I detected in wastewater extracts using high-resolution mass spectrometry approaches. Results showed that application of multiple computational mass spectrometric tools to structural elucidation of unknown organic pollutants arising in wastewaters improved the efficiency and veracity of screening approaches based on high-resolution mass spectrometry. Furthermore, structural similarity searching was essential for prioritizing substances sharing structural features with known organic pollutants or industrial and consumer chemicals that could enter the environment through use or disposal.
I then applied this comprehensive methodological and computational non-targeted analysis workflow to micropollutant fate analysis in domestic wastewaters (Chapter 3), surface waters impacted by water reuse activities (Chapter 4) and effluents of wastewater treatment facilities receiving wastewater from oil and gas extraction activities (Chapter 5). In Chapter 3, I showed that application of chemometric tools aided in the prioritization of non-targeted compounds arising at various stages of conventional wastewater treatment by partitioning high dimensional data into rational chemical categories based on knowledge of organic chemical fate processes, resulting in the classification of organic micropollutants based on their occurrence and/or removal during treatment. Similarly, in Chapter 4, high-resolution sampling and broad-spectrum targeted and non-targeted chemical analysis were applied to assess the occurrence and fate of organic micropollutants in a water reuse application, wherein reclaimed wastewater was applied for irrigation of turf grass. Results showed that organic micropollutant composition of surface waters receiving runoff from wastewater irrigated areas appeared to be minimally impacted by wastewater-derived organic micropollutants. Finally, Chapter 5 presents results of the comprehensive organic chemical composition of oil and gas wastewaters treated for surface water discharge. Concurrent analysis of effluent samples by complementary, broad-spectrum analytical techniques, revealed that low-levels of hydrophobic organic contaminants, but elevated concentrations of polymeric surfactants, which may effect the fate and analysis of contaminants of concern in oil and gas wastewaters.
Taken together, my work represents significant progress in the characterization of polar organic chemical pollutants associated with wastewater-impacted environments by high-resolution mass spectrometry. Application of these comprehensive methods to examine micropollutant fate processes in wastewater treatment systems, water reuse environments, and water applications in oil/gas exploration yielded new insights into the factors that influence transport, transformation, and persistence of organic micropollutants in these systems across an unprecedented breadth of chemical space.
Resumo:
Social structure is a key determinant of population biology and is central to the way animals exploit their environment. The risk of predation is often invoked as an important factor influencing the evolution of social structure in cetaceans and other mammals, but little direct information is available about how cetaceans actually respond to predators or other perceived threats. The playback of sounds to an animal is a powerful tool for assessing behavioral responses to predators, but quantifying behavioral responses to playback experiments requires baseline knowledge of normal behavioral patterns and variation. The central goal of my dissertation is to describe baseline foraging behavior for the western Atlantic short-finnned pilot whales (Globicephala macrohynchus) and examine the role of social organization in their response to predators. To accomplish this I used multi-sensor digital acoustic tags (DTAGs), satellite-linked time-depth recorders (SLTDR), and playback experiments to study foraging behavior and behavioral response to predators in pilot whales. Fine scale foraging strategies and population level patterns were identified by estimating the body size and examining the location and movement around feeding events using data collected with DTAGs deployed on 40 pilot whales in summers of 2008-2014 off the coast of Cape Hatteras, North Carolina. Pilot whales were found to forage throughout the water column and performed feeding buzzes at depths ranging from 29-1176 meters. The results indicated potential habitat segregation in foraging depth in short-finned pilot whales with larger individuals foraging on average at deeper depths. Calculated aerobic dive limit for large adult males was approximately 6 minutes longer than that of females and likely facilitated the difference in foraging depth. Furthermore, the buzz frequency and speed around feeding attempts indicate this population pilot whales are likely targeting multiple small prey items. Using these results, I built decision trees to inform foraging dive classification in coarse, long-term dive data collected with SLTDRs deployed on 6 pilot whales in the summers of 2014 and 2015 in the same area off the coast of North Carolina. I used these long term foraging records to compare diurnal foraging rates and depths, as well as classify bouts with a maximum likelihood method, and evaluate behavioral aerobic dive limits (ADLB) through examination of dive durations and inter-dive intervals. Dive duration was the best predictor of foraging, with dives >400.6 seconds classified as foraging, and a 96% classification accuracy. There were no diurnal patterns in foraging depth or rates and average duration of bouts was 2.94 hours with maximum bout durations lasting up to 14 hours. The results indicated that pilot whales forage in relatively long bouts and the ADLB indicate that pilot whales rarely, if ever exceed their aerobic limits. To evaluate the response to predators I used controlled playback experiments to examine the behavioral responses of 10 of the tagged short-finned pilot whales off Cape Hatteras, North Carolina and 4 Risso’s dolphins (Grampus griseus) off Southern California to the calls of mammal-eating killer whales (MEK). Both species responded to a subset of MEK calls with increased movement, swim speed and increased cohesion of the focal groups, but the two species exhibited different directional movement and vocal responses. Pilot whales increased their call rate and approached the sound source, but Risso’s dolphins exhibited no change in their vocal behavior and moved in a rapid, directed manner away from the source. Thus, at least to a sub-set of mammal-eating killer whale calls, these two study species reacted in a manner that is consistent with their patterns of social organization. Pilot whales, which live in relatively permanent groups bound by strong social bonds, responded in a manner that built on their high levels of social cohesion. In contrast, Risso’s dolphins exhibited an exaggerated flight response and moved rapidly away from the sound source. The fact that both species responded strongly to a select number of MEK calls, suggests that structural features of signals play critical contextual roles in the probability of response to potential threats in odontocete cetaceans.