An Investigation of Canadian Greenhouse Climate Prediction using Time Series

Abstract

Due to the increasing global warming trend, the greenhouse effect is becoming more and more serious, which caused a very hot summer around the world. This study aims to identify the most important factors contributing to global warming by investigating and predicting greenhouse gas (GHG) emissions. There are not many studies to predict Canada's future GHG emissions. Therefore, It was decided to use the ARIMA model in a time series analysis to predict and simulate GHG emissions in Canada. A dataset containing seven different aspects of Canadian GHG emissions over the past 27 years was used. The result shows that overall emissions will continue to rise but the growth rate of GHG emissions will decline. Among them, Agriculture and Transportation are the two influencing factors that will increase GHG emissions the most in the future. In general, to reduce GHG emissions in the future, people need to live a low-carbon life and reduce unnecessary means of transportation or use more energy-saving resources such as electric cars. For agriculture, it takes less land to produce more food, such as hybrid rice in China. The fundamental reason is that the earth's population keeps increasing, people need more private cars to travel easily, and more food, thus increasing the area of arable land but reducing the area of green forest.