Investigating global surface temperature from the perspectives of environmental, demographic, and economic...

Anthropogenic activities have increased atmospheric concentrations of greenhouse gas emissions, which have observably increased global temperature. Recognizing it as one of the most critical issues caused by human activities, this study investigates the effects of environmental, demographic, and economic indicators on global and regional temperature. For this purpose, advanced and powerful machine learning techniques, such as ANN, CNN, SVM, and LSTM, are employed using the data from 1980 to 2018 of the aforementioned regions to predict and forecast global and regional temperatures in Africa, Asia, Europe, North America, and South America. First, the predicted results were found very close to the actual surface temperature, confirming that environmental, economic, and demographic indicators are critical drivers of climate change. Second, this study forecasted global temperature from 2023 to 2050 and regional temperature from 2022 to 2050. The results also predicted a considerable increase in global temperature and regional temperature in the forthcoming years. Particularly, Asia and Africa may experience extreme weather in the future with an increase of more than 1.6 °C. Based on the findings of this study, the major implications have been that maintaining greenhouse gas emissions, balancing economic development, urbanization, and environmental quality while reducing fossil fuel energy consumption will ensure climate mitigation. The findings demand an alteration in human behavior regarding fossil fuel energy consumption to control greenhouse gas emissions, which is the most significant contributor to climate change.