Energy-related carbon dioxide emission forecasting of four European countries by employing data-driven methods
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Energy‑related carbon dioxide emission forecasting of four European countries by employing data‑driven methods Mohammad Ghalandari1,2 · Habib Forootan Fard3 · Ali Komeili Birjandi4 · Ibrahim Mahariq5 Received: 19 July 2020 / Accepted: 30 October 2020 © Akadémiai Kiadó, Budapest, Hungary 2020
Abstract Carbon dioxide emission of countries is deeply dependent on the energy system. Share of different energy resources in primary energy consumption of the countries has principal role in the emission of energy-related carbon dioxide. As well as energy consumption, the level of economic activities performs substantial role in the emission of greenhouse gases. By using data-driven methods such as artificial neural networks (ANNs), the emission of greenhouse gases can be precisely modeled. In this work, two types of ANNs, group method of data handling (GMDH) and multi-layer perceptron (MLP), are employed for estimating carbon dioxide, as one of the most important greenhouse gases, emission of four European countries including UK, Germany, Italy and France; in this regard, consumptions of various energy resources in addition to GDP, as an indicator for economic activities, of the mentioned countries are used as the inputs for modeling and forecasting. Comparison of the actual and predicted data reveals great performance of the employed approaches in modeling. R-squared values of the regression by using both GMDH and MLP are 0.9999. In addition, according to the values of average relative error of the models, it is found that using MLP is preferred due to its lower value compared with GMDH. Obtained values of absolute relative deviations of GMDH and MLP models are 0.39% and 0.33%, respectively. Keywords Artificial neural network · Greenhouse gases · Carbon dioxide · Renewable energies
Introduction Reducing the emission of greenhouse gases including carbon dioxide, carbon monoxide and NOx is one of the main concerns of several studies. Since energy consumption, especially fossil fuels, has significant role in the production of greenhouse gases, various renewable energy-based * Ali Komeili Birjandi [email protected]; [email protected] Habib Forootan Fard [email protected] 1
Institute of Research and Development, Duy Tan University, Da Nang 550000, Vietnam
2
Faculty of Electrical‑Electronic Engineering, Duy Tan University, Da Nang 550000, Vietnam
3
Department of Renewable Energies, Faculty of New Sciences and Technologies, University of Tehran, Tehran, Iran
4
Department of Civil, Geo and Environmental Engineering, Technical University of Munich, Munich, Germany
5
College of Engineering and Technology, American University of the Middle East, Egaila, Kuwait
technologies with lower emission have been developed in recent years [1, 2]. Energy systems utilizing renewable sources are widely used in order to resolve the environmental issues related to combustion of fossil fuels. In this regard, different types of renewable energy-based technologies have been employed for power production such
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