Effects of Carbon Dioxide (CO2) Emissions on People’s Death and Global Warming

Vattolly, Jose Geo (2023) Effects of Carbon Dioxide (CO2) Emissions on People’s Death and Global Warming. Masters thesis, Dublin, National College of Ireland.

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Abstract

A thorough study forecasting and analyzing the most important environmental indicators around the world are presented in this report, backed up by state-of-the-art Machine learning and Deep Learning technologies. The new strategy, based on the forecasting of anomalies, emissions of CO2, and premature death due to pollution, uses cutting-edge tools for dealing with a complicated relationship between environmental factors and human health. Our model has a wide variety of information from across continents so that it can form robust forecasting frameworks. Using machine learning, we've been able to predict accurately global anomalies and provide insight into climatic fluctuations and their possible consequences. In addition, we can find out in detail what regions are contributing to environmental degradation through our deeper learning algorithms which precisely predict CO2 emissions from all continents. By projecting the rate of mortality attributable to pollution, this study has expanded its scope into the field of health. By incorporating advanced Deep Learning architectures in our algorithms, we are able to identify complex patterns that link pollution levels with negative health impacts and give important information on the use of Public Health measures. The findings of this study will help us better understand global dynamics in the environment, and give a platform to inform policymaking. Our models' ability to predict and contribute to the development of tailored actions for environmental protection can be helpful in societies that are facing climate change and pollution challenges.

Item Type:	Thesis (Masters)
Supervisors:	Name Email Hafeez, Taimur UNSPECIFIED
Uncontrolled Keywords:	Global Anomalies; CO2 Emissions; Pollution-Related Death Rates; Machine Learning; Deep Learning
Subjects:	Q Science > QA Mathematics > Electronic computers. Computer science T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science R Medicine > RA Public aspects of medicine > RA0421 Public health. Hygiene. Preventive Medicine G Geography. Anthropology. Recreation > GE Environmental Sciences > Environment Q Science > Q Science (General) > Self-organizing systems. Conscious automata > Machine learning
Divisions:	School of Computing > Master of Science in Data Analytics
Depositing User:	Ciara O'Brien
Date Deposited:	26 May 2025 08:24
Last Modified:	26 May 2025 08:24
URI:	https://norma.ncirl.ie/id/eprint/7636

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