GIS-Based trend analysis on renewal energy consumption and production in Africa
In Africa, there has been a rise in human activities because of technological advancements and population growth, which have led to the transformation of some African villages into towns and towns into cities, increasing the region's energy demand. Utilization of advanced and appropriate renewa...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Penerbit Universiti Kebangsaan Malaysia
2024
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| Online Access: | http://journalarticle.ukm.my/24112/1/181_196%20Paper_13.pdf http://journalarticle.ukm.my/24112/ http://www.ukm.my/jqma |
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| Institution: | Universiti Kebangsaan Malaysia |
| Language: | English |
| Summary: | In Africa, there has been a rise in human activities because of technological advancements and population growth, which have led to the transformation of some African villages into towns and towns into cities, increasing the region's energy demand. Utilization of advanced and appropriate renewable energy technologies stands as a critical solution to address the increasing energy demand in Africa. This study employs GIS-based analysis to examine the evolution and shifts in renewable energy generation and consumption within the region from 1990 to 2020, to enhance awareness of the geospatial aspects of energy dynamics. The analysis detects a shift in both renewable production (REP) and renewable energy consumption (REC) over the past four decades in Africa, which signifies growth in both sections. In many cases, a disparity was observed between the renewable energy consumed and that produced, while REP, REC, and GDP have increased significantly across the continent in recent years. In addition, two models are estimated, and the results found a significant growth relationship between renewable energy production (REP) and GDP, and feedback relationships were confirmed between GDP and CO2_EM. REP improves environmental degradation, and REC has a negative impact on GDP. This study recommends further research and investigation of the data, as GIS statistical analysis still needs more attention to statistics such as the evaluation of neighboring relationships between entities and effects using spatial models. |
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