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- Member of: Theses and Dissertations
In this dissertation, I have synthesized the present state of knowledge and application of uncertainty and variability in ‘attributional’ LCA, and contribute to its quantitative assessment.
Firstly, the present state of addressment of uncertainty and variability in LCA is consolidated and reviewed. It is evident that sources of uncertainty and variability exist in the following areas: ISO standards, supplementary guides, software tools, life cycle inventory (LCI) databases, all four methodological phases of LCA, and use of LCA information. One source of uncertainty and variability, each, is identified, selected, quantified, and its implications discussed.
The use of surrogate LCI data in lieu of missing dataset(s) or data-gaps is a source of uncertainty. Despite the widespread use of surrogate data, there has been no effort to (1) establish any form of guidance for the appropriate selection of surrogate data and, (2) estimate the uncertainty associated with the choice and use of surrogate data. A formal expert elicitation-based methodology to select the most appropriate surrogates and to quantify the associated uncertainty was proposed and implemented.
Product-evolution in a non-uniform manner is a source of temporal variability that is presently not considered in LCA modeling. The resulting use of outdated LCA information will lead to misguided decisions affecting the issue at concern and eventually the environment. In order to demonstrate product-evolution within the scope of ISO 14044, and given that variability cannot be reduced, the sources of product-evolution were identified, generalized, analyzed and their implications (individual and coupled) on LCA results are quantified.
Finally, recommendations were provided for the advancement of robustness of 'attributional' LCA, with respect to uncertainty and variability.
The article highlights the damage COVID-19 can cause by attacking brain tissue which can lead to several neurological disorders; it is a collection of systematic review and meta-analysis reviews as well as different scientific studies. The article addresses the background of COVID-19 and the distinction between Long COVID and COVID-19, along with the general pathway that the virus of COVID-19 takes to infect a cell at a cellular level. The variety of symptoms that individuals experience can be a topic of interest, and this article discusses the variability in COVID-19 infection. Moreover, SARS-COV-2 can enter the body in different ways and attack different types of cells within the body, thus the article brings attention to the different mechanisms of infection. Due to the brain damage that can be caused by COVID-19, there are several neurological disorders the article addresses including status epilepticus, stroke, acute necrotizing encephalopathy, encephalitis, hypogeusia, hyposmia, guillain-barre syndrome, and systemic inflammatory response syndrome. Although these disorders have different routes of treatment, the article briefly talks about general treatments for COVID-19 that include antiviral drugs, immune modulators, and monoclonal antibody treatment. Given the significance of COVID-19, more research should be done to understand the variety of neurological disorders that can be an effect of COVID-19 infection.