Evaluating Environmental Taxes and CO2 Emission Reduction in the UK: A Neural Network Approach

Abstract

This paper aims to determine the effects of environmental taxes on CO2 emissions in the United Kingdom (UK). To determine their effectiveness in reducing carbon emissions depending on Neural Networks algorithms as a machine learning algorithm. The paper approved the strong negative relationship between CO2 emissions and Taxes on Pollution, Taxes on Resources, Taxes on Transport, and Taxes on Energy. This indicates the potential of these taxes and their positive results in reducing carbon emissions in the United Kingdom. Also, the paper approved that the taxes on pollution have the highest effects on CO2 emissions at 28.6%, followed by taxes on resources at 25%, taxes on transport at 23.7%, and taxes on energy at 22.8%. So, the UK policymakers should maximize depending on taxes on pollution compared to other taxes And rely on other types in order of influence.