Analysis of Changes in Atmospheric CO2 Emissions Using Prophet Facebook - Primandari, Arum Handini; Thalib, Achmad Kurniansyah; Kesumawati, Ayundyah (Enthusiastic : International Journal of Applied Statistics and Data Science, 2022)
CO2 emissions have been an environmental issue for decades. The trigger for the increasing concentration of CO2 in the atmosphere is the growth of industries related to burning fossil fuels for coal, natural gas, and petroleum. For nearly a century, several attempts have been made to suppress the rapid growth of CO2 . This study uses daily atmospheric  CO2  levels observed in  Mauna Loa laboratories. The method used is a Prophet that can handle seasonality and mark the change points. Almost 20% of data was missing value, which was then imputed using spline interpolation. Based on the analysis results,  CO2 levels have an upward trend throughout the year and seasonality. There is no point of change in the last ten years that shows a decrease in  CO2  levels. Using forward chaining cross-validation evaluation and error measurement, the prophet model can follow the pattern of  CO2  levels well. The average RMSE value is less than 2.0, with an MAPE value bellow 0.5%.