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Sustainability 2018, 10(9), 3110; https://doi.org/10.3390/su10093110

Analyzing the Impact of GDP on CO2 Emissions and Forecasting Africa’s Total CO2 Emissions with Non-Assumption Driven Bidirectional Long Short-Term Memory

1,2,* and 1,2
1
School of Management and Economics, University of Electronic Science and Technology of China, No. 2006, Xiyuan Ave, West Hi-Tech Zone, Chengdu 611731, Sichuan, China
2
Center for West African Studies, University of Electronic Science and Technology of China, No. 2006, Xiyuan Ave, West Hi-Tech Zone, Chengdu 611731, Sichuan, China
*
Author to whom correspondence should be addressed.
Received: 23 July 2018 / Revised: 25 August 2018 / Accepted: 28 August 2018 / Published: 31 August 2018
(This article belongs to the Section Energy Sustainability)
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Abstract

The amount of total carbon dioxide (CO2) emissions emitted into the environment threatens both human and global ecosystems. Based on this background, this study first analyzed the relationship between gross domestic product (GDP) and CO2 emissions in five West African countries covering the period of 2007–2014 based on a panel data model. Our causality analysis revealed that there exists a unidirectional causality running from GDP to CO2 emissions. Second, after establishing the nexus between GDP and CO2 emissions, we forecast Africa’s CO2 emissions with the aim of projecting future consumption levels. With the quest to achieve climate change targets, realistic and high accuracy total CO2 emissions projections are key to drawing and implementing realizable environmentally-friendly energy policies. Therefore, we propose a non-assumption driven forecasting technique for long-term total CO2 emissions. We implement our bidirectional long short-term memory (BiLSTM) sequential algorithm formulation for both the testing stage (2006–2014) and forecasting stage (2015–2020) on Africa’s aggregated data as well as the five selected West African countries employed herein. We then propose policy recommendations based on the direction of causality between CO2 emissions and GDP, and our CO2 emissions projections in order to guide policymakers to implement realistic and sustainable policy targets for West Africa and Africa as a whole. View Full-Text
Keywords: CO2 emissions; bidirectional long short-term memory (BiLSTM); Africa; West Africa; diversification of energy sources; climate change; forecasting CO2 emissions; bidirectional long short-term memory (BiLSTM); Africa; West Africa; diversification of energy sources; climate change; forecasting
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
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Ameyaw, B.; Yao, L. Analyzing the Impact of GDP on CO2 Emissions and Forecasting Africa’s Total CO2 Emissions with Non-Assumption Driven Bidirectional Long Short-Term Memory. Sustainability 2018, 10, 3110.

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