CO2 Emission Trends and Drivers: A Data-Driven Analysis
DOI:
https://doi.org/10.54536/ajec.v4i1.4464Keywords:
CO₂ Emissions, Data-Driven Analysis, Environmental Sustainability, Renewable EnergyAbstract
Rising CO2 emissions remain a major global challenge, driven by industrialization, economic expansion, and fossil fuel dependency. Previous research has looked at the link between economic growth and emissions, but more needs to be done to fully understand how socioeconomic factors, industrial activity, and the use of renewable energy all affect CO2 levels. This study looks at global CO2 emissions trends using a large dataset that includes data from 195 countries from 1900 to 2023 and includes key indicators like GDP, population, urbanization, energy use, and industrial activity. There were three main analyses: (1) a scatter plot of GDP versus CO2 emissions to look at economic drivers; (2) a time-series analysis to look at historical trends in emissions; and (3) a correlation heatmap to look at how socioeconomic factors and emissions are connected. Results indicate a strong correlation between GDP and emissions, with variations influenced by renewable energy usage and industrial efficiency. Historical analysis reveals that some nations have achieved emission plateaus, suggesting the impact of policy interventions and sustainable energy adoption. Additionally, correlation analysis shows limited direct impact from urbanization and population growth, emphasizing the importance of clean energy policies and industrial regulation. The dataset addressed ethical considerations by anonymizing country identities in the dataset to protect privacy and prevent political bias. This research provides valuable insights for policymakers, climate researchers, and economists, guiding evidence-based strategies for CO2 emissions mitigation.
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