Matching Items (5)
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- All Subjects: Sewage
- Creators: Halden, Rolf
Environmental releases of neonicotinoid and fipronil insecticides via U.S. wastewater infrastructure
Description
This dissertation is focused on environmental releases from U.S. wastewater infrastructure of recently introduced, mass-produced insecticides, namely neonicotinoids as well as fipronil and its major degradates (sulfone, sulfide, amide, and desulfinyl derivatives), jointly known as fiproles. Both groups of compounds recently have caught the attention of regulatory agencies worldwide due to their toxic effects on pollinators and on aquatic invertebrates at very low, part-per-trillion levels (Chapter 1). Mass balance studies conducted for 13 U.S. wastewater treatment plants (WWTPs) showed ubiquitous occurrence (3-666 ng/L) and persistence of neonicotinoids (Chapter 2). For the years 2001 through 2016, a longitudinal nationwide study was conducted on the occurrence of fiproles, via analysis of sludge as well as raw and treated wastewater samples. Sludge analysis revealed ubiquitous fiprole occurrence since 2001 (0.2-385 µg/kg dry weight) and a significant increase (2.4±0.3-fold; p<0.005) to elevated levels found both in 2006/7 and 2015/6. This study established a marked persistence of fiproles during both wastewater and sludge treatment, while also identifying non-agricultural uses as a major source of fiprole loading to wastewater (Chapter 3). Eight WWTPs were monitored in Northern California to assess pesticide inputs into San Francisco Bay from wastewater discharge. Per-capita-contaminant-loading calculations identified flea and tick control agents for use on pets as a previously underappreciated source term dominating the mass loading of insecticides to WWTPs in sewage and to the Bay in treated wastewater (Chapter 4). A nationwide assessment of fipronil emissions revealed that pet products, while representing only 22±7% of total fipronil usage (2011-2015), accounted for 86±5% of the mass loading to U.S. surface waters (Chapter 5). In summary, the root cause for considerable annual discharges into U.S. surface waters of the neonicotinoid imidacloprid (3,700-5,500 kg/y) and of fipronil related compounds (1,600-2,400 kg/y) is domestic rather than agricultural insecticide use. Reclaimed effluent from U.S. WWTPs contained insecticide levels that exceed toxicity benchmarks for sensitive aquatic invertebrates in 83% of cases for imidacloprid and in 67% of cases for fipronil. Recommendations are provided on how to limit toxic inputs in the future.
ContributorsSadaria, Akash Mahendra (Author) / Halden, Rolf (Thesis advisor) / Fraser, Matthew (Committee member) / Perreault, Francois (Committee member) / Mascaro, Giuseppe (Committee member) / Arizona State University (Publisher)
Created2017
Description
With the recent rise in opioid overdose and death1<br/><br/>, chronic opioid therapy (COT) programs using<br/>Center of Disease Control (CDC) guidelines have been implemented across the United States8<br/>.<br/>Primary care clinicians at Mayo Clinic initiated a COT program in September of 2017, during the<br/>use of Cerner Electronic Health Record (EHR) system. Study metrics included provider<br/>satisfaction and perceptions regarding opioid prescription. Mayo Clinic transitioned its EHR<br/>system from Cerner to Epic in October 2018. This study aims to understand if provider perceptions<br/>about COT changed after the EHR transition and the reasons underlying those perceptions.
ContributorsPonnapalli, Sravya (Author) / Murcko, Anita (Thesis director) / Wallace, Mark (Committee member) / College of Health Solutions (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
Description
Uncertainty is inherent in predictive decision-making, both with respect to forecasting plausible future conditions based on a historic record, and with respect to backcasting likely upstream states from downstream observations. In the first chapter, I evaluated the status of current water resources management policy in the United States (U.S.) with respect to its integration of projective uncertainty into state-level flooding, drought, supply and demand, and climate guidance. I found uncertainty largely absent and discussed only qualitatively rather than quantitatively. In the second chapter, I turned to uncertainty in the interpretation of downstream observations as indicators of upstream behaviors in the field of Wastewater-Based Epidemiology (WBE), which has made possible the near real-time, yet anonymous, monitoring of public health via measurements of biomarkers excreted to wastewater. I found globally, seasonality of air and soil temperature causes biomarker degradation to vary up to 13-fold over the course of a year, constituting part of the background processes WBE must address, or detrend, prior to decision-making. To determine whether the seasonal change in degradation rates was introducing previously unaccounted for uncertainty with respect to differences in observed summertime and winter-time populations, I evaluated demographic indicators recorded by the Census Bureau for correlation with their distance from all major wastewater treatment plants across the U.S. The analysis identified statistically significant correlation for household income, education attainment, unemployment, military service, and the absence of health insurance. Finally, the model was applied to a city-wide case study to test whether temperature could explain some of the trends observed in monthly observations of two opiate compounds. Modeling suggests some of the monthly changes were attributed to natural temperature fluctuation rather than to trends in the substances’ consumption, and that uncertainty regarding discharge location can dominate even relative observed differences in opiate detections. In summary, my work has found temperature an important modulator of WBE results, influencing both the type of populations observed and the likelihood of upstream behaviors disproportionally magnified or obscured, particularly for the more labile biomarkers. There exists significant potential for improving the understanding of empirical observations via numerical modeling and the application of spatial analysis tools.
ContributorsHart, Olga (Author) / Halden, Rolf (Thesis advisor) / Mascaro, Giuseppe (Committee member) / Renaut, Rosemary (Committee member) / Nelson, Keith (Committee member) / Arizona State University (Publisher)
Created2019
Description
Alzheimer’s disease (AD) is a neurodegenerative disease resulting in loss of cognitive function and is not considered part of the typical aging process. Recently, research is being conducted to study environmental effects on AD because the exact molecular mechanisms behind AD are not known. The associations between various toxins and AD have been mixed and unclear. In order to better understand the role of the environment and toxic substances on AD, we conducted a literature review and geospatial analysis of environmental, specifically wastewater, contaminants that have biological plausibility for increasing risk of development or exacerbation of AD. This literature review assisted us in selecting 10 wastewater toxic substances that displayed a mixed or one-sided relationship with the symptoms or prevalence of Alzheimer’s for our data analysis. We utilized data of toxic substances in wastewater treatment plants and compared them to the crude rate of AD in the different Census regions of the United States to test for possible linear relationships. Using data from the Targeted National Sewage Sludge Survey (TNSSS) and the Centers for Disease Control and Prevention (CDC), we developed an application using R Shiny to allow users to interactively visualize both datasets as choropleths of the United States and understand the importance of this area of research. Pearson’s correlation coefficient was calculated resulting in arsenic and cadmium displaying positive linear correlations with AD. Other analytes from this statistical analysis demonstrated mixed correlations with AD. This application and data analysis serve as a model in the methodology for further geospatial analysis on AD. Further data analysis and visualization at a lower level in terms of scope is necessary for more accurate and reliable evidence of a causal relationship between the wastewater substance analytes and AD.
GitHub Repository: https://github.com/komal-agrawal/AD_GIS.git
GitHub Repository: https://github.com/komal-agrawal/AD_GIS.git
ContributorsAgrawal, Komal (Author) / Scotch, Matthew (Thesis director) / Halden, Rolf (Committee member) / College of Health Solutions (Contributor, Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
Description
The Future of Wastewater Sensing workshop is part of a collaboration between Arizona State University Center for Nanotechnology in Society in the School for the Future of Innovation in Society, the Biodesign Institute’s Center for Environmental Security, LC Nano, and the Nano-enabled Water Treatment (NEWT) Systems NSF Engineering Research Center. The Future of Wastewater Sensing workshop explores how technologies for studying, monitoring, and mining wastewater and sewage sludge might develop in the future, and what consequences may ensue for public health, law enforcement, private industry, regulations and society at large. The workshop pays particular attention to how wastewater sensing (and accompanying research, technologies, and applications) can be innovated, regulated, and used to maximize societal benefit and minimize the risk of adverse outcomes, when addressing critical social and environmental challenges.
ContributorsWithycombe Keeler, Lauren (Researcher) / Halden, Rolf (Researcher) / Selin, Cynthia (Researcher) / Center for Nanotechnology in Society (Contributor)
Created2015-11-01