Carbon dioxide emissions prediction of five Middle Eastern countries using artificial neural networks

ABSTRACT

Greenhouse gas (GHG) emissions contribute considerably to global warming and climate change. Since energy systems notably influence GHG emissions, such emissions can be modeled at the national level based on the energy sources utilized by a country. Economic activity also affects GHG emissions. In this work, an Artificial Neural Network (ANN) approach, Group Method of Data Handling (GMDH), is used for determining emissions of carbon dioxide, the most significant GHG, on the basis of shares of various energy sources used as primary energy supply and GDP as an indicator of economic activity. Five countries are considered as case studies: Iran, Kuwait, Qatar, Saudi Arabia, and United Arab Emirates (UAE). Comparing the results achieved by the developed model and actual quantities shows that the ANN model has acceptable accuracy for predicting CO₂ emissions. The average absolute relative error and the R-squared values of the GMDH model are 2.3% and 0.9998, respectively. These values demonstrate the precision of the model in forecasting emissions of CO₂.

KEYWORDS:

• Artificial Neural Network
• greenhouse gases
• GMDH
• Middle Eastern countries
• carbon dioxide emission

Author Contributions

All authors contributed equally to the paper.

Conflicts of Interest

The authors declare no conflict of interest.

Additional information

Notes on contributors

Mohammad Hossein Ahmadi

Mohammad Hossein Ahmadi received his PhD degree from University of Tehran in 2016. Presently, he works as an Assistant Professor at Shahrood University of Technology in the department of Mechanical Engineering. He published more than 200 articles in international journals.

Hamidreza Jashnani

Hamidreza Jashnani received his aerospace engineering (MSc) degree at the Amirkabir University of Technology in 2015. Presently, he studies aerospace Ph.D. in Islamic Azad University, Science and Research Branch, Tehran. Also, he works as an Air Traffic controller at Mehrabad International Airport.

Kwok-Wing Chau

Kwok-Wing Chau is currently Professor in Department of Civil and Environmental Engineering of The Hong Kong Polytechnic University. He is very active in undertaking research works and the scope of his research interest is very broad, covering numerical flow modeling, water quality modeling, hydrological modeling, use of artificial intelligence in water resources engineering, etc.

Ravinder Kumar

Ravinder Kumar is currently Associate Professor in Department of Mechanical Engineering of ‎Lovely Professional University. He is very active in undertaking research works and the scope of his research interest is very broad, covering numerical flow modeling, thermodynamics, sustainable energy, and the environmental impact of energy systems, etc.

Marc A. Rosen

Marc A. Rosen is a Professor in the Faculty of Engineering and Applied Science at the University of Ontario Institute of Technology in Oshawa, Canada. He served as founding Dean from of the Faculty from 2002-08. Dr. Rosen has served as President of the Engineering Institute of Canada (2008-10) and the Canadian Society for Mechanical Engineering (2002-04), and is a registered Professional Engineer in Ontario. Dr. Rosen is an active teacher and researcher in thermodynamics, sustainable energy, and the environmental impact of energy systems. Much of his research has been carried out for industry.