Forecasting CO2 Emission in the US Using Regression Models

Abstract

Our paper examines CO2 emissions resulting from energy consumption across key sectors: commercial, industrial, transportation, residential, and electrical. We emphasize predicting CO2 output associated with diverse fuel types used within these sectors. Leveraging extensive datasets from the Energy Information Administration and the Environmental Protection Agency, we utilize energy consumption data, measured in Trillion Btu units, to build predictive models that forecast future CO2 emissions. By analyzing the correlation between energy use and CO2 output, our study provides critical insights into the environmental impact of different fuel sources. We incorporate the polluting factors of each energy type to estimate their individual contributions to overall emissions. These models empower stakeholders to make informed decisions regarding energy use, fostering proactive environmental control. Our work advocates for sustainable energy practices by identifying opportunities for reducing CO2 emissions while emphasizing the importance of mindful consumption. The findings encourage transitioning to environmentally friendly energy alternatives and promote collective action toward mitigating climate change. Ultimately, this research underscores the need for balancing energy demands with environmental stewardship, aiming to inspire practices that contribute to a greener, more sustainable future for current and future generations.

Received: 3 October 2024 | Revised: 31 December 2024 | Accepted: 3 April 2025

Conflicts of Interest

The authors declare that they have no conflicts of interest to this work.

Data Availability Statement

The data that support the findings of this study are openly available in the U.S. Energy Information Administration at www.eia.gov and in the United States Environmental Protection Agency at www.epa.gov.

Author Contribution Statement

Kamil Samara: Conceptualization, Methodology, Validation, Formal analysis, Investigation, Resources, Writing – original draft, Writing – review & editing, Visualization, Supervision, Project administration. Yunhwan Jeong and Thomas H. Beaupre: Conceptualization, Methodology, Software, Validation, Formal analysis, Investigation, Resources, Data curation, Writing – original draft, Writing – review & editing, Visualization.