Low carbon emissions have a great importance in our life. The increasing importance of carbon emission levels have attracted the interests of researchers and academics in the field. In this article, a panel data econometric model is developed to measure the relationship between renewable energy, energy productivity, population, urbanization, motorization, and Gross Domestic Product (GDP) per capita and their impacts on carbon dioxide CO2 emissions. Data used in this study was collected from the European Statistical Office (EUROSTAT) and five statistical hypotheses were tested and validated through a multilinear regression model using the Econometric Views (Eviews) 10.0 statistical software. The Hausman test was used to choose between a model with fixed effects and a model with random effects, and the variance inflection factor (VIF) was used to test the collinearity between the independent variables. The author’s findings indicate that renewable energy at the European Union (EU) level has a positive impact on low-carbon emissions. It was found that a 1% increase in renewable energy consumption would reduce the CO2 emissions by 0.11 million tons, while population growth and urbanization degree add more restrictions to the econometric equation of the impact on carbon emissions.