The primary goal of this study was to assess the temporal variations, trends, and aberrations in the greenhouse gas (GHG) series for Canada from a regional and economic sector perspective. A Bayesian Change Point method based on the Markov Chain Monte Carlo method and Binary Segmentation were used to detect aberrations, the number of changes, and locations. Trend analysis and change point results show that all the Prairie provinces have uptrends and frequent change points. On the other hand, Central, Atlantic, and the Territories show evidence of a downtrend. There is a consistent uptrend and frequent change points for the economic sectors in the oil and gas, agriculture, transportation, and building economic sectors. This upward trend could be due to a consistent increase in petroleum extraction, increased population, and increased number of on-road cars. The increase in the agriculture sector could be due to an increase in livestock products and the application of fertilizer and manure for farming purposes, especially in the Prairie jurisdictions. From the foregoing, Canada's abundant water resources potential will be crucial in mitigating GHG emission in the heat and electricity sector across various jurisdictions.