The impact of certain factors on the changes in atmospheric carbon dioxide (CO₂) concentrations has yet to be elucidated. In particular, the impacts of sea surface temperature (SST) on the balance of CO₂ emissions and absorption in the atmosphere and the human use of fossil fuels have not been rigorously compared. In this study, the impact of each factor was examined using multivariate analysis. Publicly available data from prominent climate research and energy-related organizations were used. Multiple linear regression analysis was performed using the annual changes in atmospheric CO₂ levels for each year as the objective variable. The SST and human emissions for each year were the explanatory factors. After 1959, the model using the SST derived from NASA best represented the annual CO₂ increase (regression coefficient B = 2.406, P < 0.0002, model R² = 0.663, P < 7e-15). However, human emissions were not a determining factor in any of the regression models. Furthermore, the atmospheric CO₂ concentration predicted, using the regression equation obtained for the SST derived from UK-HADLEY centre after 1960, showed an extremely high correlation with the actual CO₂ concentration (Pearson correlation coefficient r = 0.9995, P < 3e-92). The difference was 1.45 ppm in 2022. In conclusion, this study is the first to use multiple regression analysis to demonstrate that the independent determinant of the annual
increase in atmospheric CO₂ concentration was SST, which showed strong predictive ability. However, human CO₂ emissions were irrelevant. This result indicates that atmospheric CO₂ has fluctuated as natural phenomenon, regardless of human activity.
