Analysing the Impact of Engine Size on CO2 Emissions in Five-Seater Vehicles Using Machine Learning Techniques

Abstract

The release of carbon emissions into the atmosphere has a negative impact on the environment. Carbon emissions are considered a significant factor in global warming. These harmful emissions trap heat and lead to an increase in the earth's average temperatures, which in turn causes melting polar ice caps, rising sea levels, and severe weather patterns. Fiveseater vehicles represent a significant portion of the global automotive fleet, making their emissions impactful in contributing to these environmental changes. This study investigates the relationship between engine size and CO2 emissions in five-seater vehicles using machine learning algorithms. Linear regression, ElasticNet, and neural networks were applied to a dataset of 38, 500 observations obtained from Kaggle. The study found a significant correlation between engine sizes and CO2 emissions. Factors such as engine displacement and fuel type were analysed and identified as contributors to CO2 emissions. The results indicate that advanced engine technologies such as turbochargers and hybrid systems can mitigate emissions by improving efficiency although the impact varies. These findings highlight the importance of engine downsizing and technological integration to reduce the automotive sector's carbon footprint. This study offers insights that can help guide environmentally-friendly strategies in the automotive industry. 

https://doi.org/10.59200/ICONIC.2024.024