Email this article Climate Risks and Economic Consequences of Rising Global CO2 Emissions in Aviation, Shipping, and Heavy-Duty Transport
Abstract
This study examines methods to lessen the environmental consequences of global CO2 emissions from the hard-to-abate transport sector. The paper analyzed historical and projected trends in global CO2 emissions from the hard-to-abate transport industry under two scenarios: the stated policy scenario (STEPS) and the announced pledged scenario (APS). The study covered the historical period from 2010 to 2022 and projected emissions up to 2050. The analysis revealed that the compound annual growth rate (CAAGR) of STEP exceeded that of APS in 2030 and 2050 for challenging emissions from heavy- duty vehicles, aircraft, and shipping when compared to the baseline year of 2022. The aviation industry has a higher CAAGR of 5.3% and 2.5% for 2030 and 2050, respectively, compared to heavy-duty vehicles at 1.6% and 0.9% for 2030 and 2050, respectively, and shipping at 0.7% and 0.9% for 2030 and 2050, respectively, under STEPS. Under the APS scenario, shipping showed a negative CAAGR of -0.8% and -2.8% for 2030 and 2050, respectively, and 0.4% and -1.8% for 2030 and 2050, respectively, for heavy-duty trucks. In comparison, the aviation industry had CAAGRs of 4.5% and 0.8% for 2030 and 2050, respectively. The data shows that the aviation industry is expected to see a far greater CAAGR in emissions than heavy-duty vehicles and shipping in both STEPS and APS scenarios. Targeted efforts are necessary to mitigate the environmental effects of air travel in the upcoming decades. The paper also examined 56 publicly traded international transportation companies and their corresponding carbon emission targets. Only seven companies, or 12.5%, have established goals for reducing emissions from 2023 to 2050; 10 companies, accounting for 17.9%, have committed to achieving carbon neutrality by 2040 to 2060; five corporations, representing 8.9%, have set targets for reducing emission intensity from 2025 to 2034; and 34 global corporations, making up 60.7%, have committed to achieving net zero emissions between 2040 and 2050. Despite some progress in setting emission reduction targets in the air travel industry, many companies still need to set carbon footprint reduction goals.
Citation: Eyime, E., & Ushie, O. (2024). Climate Risks and Economic Consequences of Rising Global CO2 Emissions in Aviation, Shipping, and Heavy-Duty Transport. Trends in Renewable Energy, 11(1), 84-121. doi:http://dx.doi.org/10.17737/tre.2025.11.1.00188
Keywords
Full Text:
FULL TEXT (PDF)References
Kwilinski, A., Lyulyov, O., & Pimonenko, T. (2024). Reducing transport sector CO2 emissions patterns: Environmental technologies and renewable energy. Journal of Open Innovation: Technology, Market, and Complexity, 10(1), 100217. doi:https://doi.org/10.1016/j.joitmc.2024.100217
Solaymani, S. (2022). CO2 emissions and the transport sector in Malaysia. Frontiers in Environmental Science, 9, 774164. doi:https://doi.org/10.3389/fenvs.2021.774164
Ahmed, S., Ahmed, K., & Ismail, M. (2020). Predictive analysis of CO2 emissions and the role of environmental technology, energy use and economic output: evidence from emerging economies. Air Quality, Atmosphere & Health, 13(9), 1035-1044. doi:https://doi.org/10.1007/s11869-020-00855-1
Nwokolo, S. C., Meyer, E. L., & Ahia, C. C. (2023). Credible pathways to catching up with climate goals in Nigeria. Climate, 11(9), 196. doi:https://doi.org/10.3390/cli11090196
Nwokolo, S. C., Singh, R., Khan, S., Kumar, A., & Luthra, S. (2023). Global Investment and Development in Africa. In Africa's Path to Net-Zero: Exploring Scenarios for a Sustainable Energy Transition (pp. 15-58). Cham: Springer Nature Switzerland. doi:https://doi.org/10.1007/978-3-031-44514-9_2
Wang, L., Xue, X., Zhao, Z., Wang, Y., & Zeng, Z. (2020). Finding the de-carbonization potentials in the transport sector: application of scenario analysis with a hybrid prediction model. Environmental Science and Pollution Research, 27(17), 21762-21776. doi:https://doi.org/10.1007/s11356-020-08627-1
Alataş, S. (2022). Do environmental technologies help to reduce transport sector CO2 emissions? Evidence from the EU15 countries. Research in Transportation Economics, 91, 101047. doi:https://doi.org/10.1016/j.retrec.2021.101047
Amin, A., Altinoz, B., & Dogan, E. (2020). Analyzing the determinants of carbon emissions from transportation in European countries: the role of renewable energy and urbanization. Clean Technologies and Environmental Policy, 22(8), 1725-1734. doi:https://doi.org/10.1007/s10098-020-01910-2
Awan, A., Alnour, M., Jahanger, A., & Onwe, J. C. (2022). Do technological innovation and urbanization mitigate carbon dioxide emissions from the transport sector? Technology in Society, 71, 102128. doi:https://doi.org/10.1016/j.techsoc.2022.102128
Wang, C., Wood, J., Wang, Y., Geng, X., & Long, X. (2020). CO2 emission in transportation sector across 51 countries along the Belt and Road from 2000 to 2014. Journal of Cleaner Production, 266, 122000. doi:https://doi.org/10.1016/j.jclepro.2020.122000
Nwokolo, S. C., Singh, R., Khan, S., Kumar, A., & Luthra, S. (2023). Scenarios that Could Give Rise to an African Net-Zero Energy Transition. In Africa's Path to Net-Zero: Exploring Scenarios for a Sustainable Energy Transition (pp. 263-298). Cham: Springer Nature Switzerland. doi: https://doi.org/10.1007/978-3-031-44514-9_8
Nwokolo, S., Eyime, E., Obiwulu, A., & Ogbulezie, J. (2024). Africa's Path to Sustainability: Harnessing Technology, Policy, and Collaboration. Trends in Renewable Energy, 10(1), 98-131. doi:http://dx.doi.org/10.17737/tre.2024.10.1.00166
Barman, P., Dutta, L., Bordoloi, S., Kalita, A., Buragohain, P., Bharali, S., & Azzopardi, B. (2023). Renewable energy integration with electric vehicle technology: A review of the existing smart charging approaches. Renewable and Sustainable Energy Reviews, 183, 113518. doi:https://doi.org/10.1016/j.rser.2023.113518
Borysova, T., Monastyrskyi, G., Zielinska, A., & Barczak, M. (2019). Innovation activity development of urban public transport service providers: multifactor economic and mathematical model. Marketing and Management of Innovations, 4, 98-109. doi:http://doi.org/10.21272/mmi.2019.4-08
Fontanot, T., Kishore, R., Van den Kerkhof, S., Blommaert, M., Peremans, B., Dupon, O., . . . Meuret, Y. (2024). Multi-physics based energy yield modelling of a hybrid concentrated solar power/photovoltaic system with spectral beam splitting. Solar Energy, 278, 112753. doi:https://doi.org/10.1016/j.solener.2024.112753
Godil, D. I., Yu, Z., Sharif, A., Usman, R., & Khan, S. A. R. (2021). Investigate the role of technology innovation and renewable energy in reducing transport sector CO emission in China: A path toward sustainable development. Sustainable Development, 29(4), 694-707. doi:https://doi.org/10.1002/sd.2167
Nwokolo, S. C., Singh, R., Khan, S., Kumar, A., & Luthra, S. (2023). Decarbonizing Hard-to-Abate Sectors in Africa. In Africa's Path to Net-Zero: Exploring Scenarios for a Sustainable Energy Transition (pp. 211-236). Cham: Springer Nature Switzerland. doi:https://doi.org/10.1007/978-3-031-44514-9_6
Nwokolo, S. C., Singh, R., Khan, S., Kumar, A., & Luthra, S. (2023). Technological Pathways to Net-Zero Goals in Africa. In Africa's Path to Net-Zero: Exploring Scenarios for a Sustainable Energy Transition (pp. 93-210). Cham: Springer Nature Switzerland. doi:https://doi.org/10.1007/978-3-031-44514-9_5
Nwokolo, S. C., Singh, R., Khan, S., Kumar, A., & Luthra, S. (2023). Africa's Path to Net-Zero. Cham: Springer Nature Switzerland; 2023. doi:https://doi.org/10.1007/978-3-031-44514-9
Sadiqa, A., Gulagi, A., Bogdanov, D., Caldera, U., & Breyer, C. (2022). Renewable energy in Pakistan: Paving the way towards a fully renewables-based energy system across the power, heat, transport and desalination sectors by 2050. IET Renewable Power Generation, 16(1), 177-197. doi:https://doi.org/10.1049/rpg2.12278
Hassan, M. A., Bailek, N., Bouchouicha, K., & Nwokolo, S. C. (2021). Ultra-short-term exogenous forecasting of photovoltaic power production using genetically optimized non-linear auto-regressive recurrent neural networks. Renewable Energy, 171, 191-209. doi:https://doi.org/10.1016/j.renene.2021.02.103
Nwokolo, S. C., Singh, R., Khan, S., & Kumar, A. (2025). Chapter 4 - Technological advancements in Africa. In S. C. Nwokolo, R. Singh, S. Khan, & A. Kumar (Eds.), Technological Pathways for Africa' s Net-Zero Economy (pp. 139-157): Elsevier. doi:https://doi.org/10.1016/B978-0-443-31486-5.00004-5
Nwokolo, S. C., Singh, R., Khan, S., & Kumar, A. (2024). Technological Pathways for Africa' s Net-Zero Economy: Technology Solutions to Unlock Africa’s Sustainable Future. Elsevier Science. doi:https://doi.org/10.1016/C2023-0-52499-1
Nwokolo, S. C., Singh, R., Khan, S., & Kumar, A. (2025). Chapter 1 - State of play. In S. C. Nwokolo, R. Singh, S. Khan, & A. Kumar (Eds.), Technological Pathways for Africa' s Net-Zero Economy (pp. 1-37): Elsevier. doi:https://doi.org/10.1016/B978-0-443-31486-5.00001-X
Nwokolo, S. C., Singh, R., Khan, S., & Kumar, A. (2025). Chapter 2 - Threats to the rapidity of sustainability transitions posed by technological changes. In S. C. Nwokolo, R. Singh, S. Khan, & A. Kumar (Eds.), Technological Pathways for Africa' s Net-Zero Economy (pp. 39-75): Elsevier. doi:https://doi.org/10.1016/B978-0-443-31486-5.00002-1
Hens, L., Melnyk L., Matsenko, O., Chygryn, O., & Gonzales, C. C. (2019). Transport Economics and Sustainable Development in Ukraine. Marketing and Management of Innovations, 3, 272-284. doi:http://doi.org/10.21272/mmi.2019.3-21
Marzouk, O. A. (2024). Expectations for the Role of Hydrogen and Its Derivatives in Different Sectors through Analysis of the Four Energy Scenarios: IEA-STEPS, IEA-NZE, IRENA-PES, and IRENA-1.5°C. Energies, 17(3), 646. doi:https://doi.org/10.3390/en17030646
International Energy Agency. (2022). World Energy Outlook 2022. https://www.iea.org/reports/world-energy-outlook-2022 (accessed on 10/28/2024)
Nwokolo, S. C., Singh, R., Khan, S., & Kumar, A. (2025). Chapter 11 - Potential technological pathways for Africa's net-zero economy. In S. C. Nwokolo, R. Singh, S. Khan, & A. Kumar (Eds.), Technological Pathways for Africa' s Net-Zero Economy (pp. 283-447): Elsevier. doi: https://doi.org/10.1016/B978-0-443-31486-5.00011-2
Hickman, R., Ashiru, O., & Banister, D. (2009). Achieving Carbon-Efficient Transportation: Backcasting from London. Transportation Research Record, 2139(1), 172-182. doi:https://doi.org/10.3141/2139-20
Li, X., Ren, A., & Li, Q. (2022). Exploring Patterns of Transportation-Related CO2 Emissions Using Machine Learning Methods. Sustainability, 14(8), 4588. doi:https://doi.org/10.3390/su14084588
Ağbulut, Ü. (2022). Forecasting of transportation-related energy demand and CO2 emissions in Turkey with different machine learning algorithms. Sustainable Production and Consumption, 29, 141-157. doi:https://doi.org/10.1016/j.spc.2021.10.001
Klemm, C., & Vennemann, P. (2021). Modeling and optimization of multi-energy systems in mixed-use districts: A review of existing methods and approaches. Renewable and Sustainable Energy Reviews, 135, 110206. doi:https://doi.org/10.1016/j.rser.2020.110206
Schmidt Rivera, X. C., Topriska, E., Kolokotroni, M., & Azapagic, A. (2018). Environmental sustainability of renewable hydrogen in comparison with conventional cooking fuels. Journal of Cleaner Production, 196, 863-879. doi:https://doi.org/10.1016/j.jclepro.2018.06.033
Agyekum, E. B., Nutakor, C., Khan, T., Adegboye, O. R., Odoi-Yorke, F., & Okonkwo, P. C. (2024). Analyzing the research trends in the direction of hydrogen storage – A look into the past, present and future for the various technologies. International Journal of Hydrogen Energy, 74, 259-275. doi:https://doi.org/10.1016/j.ijhydene.2024.05.399
Aguilar-Jiménez, J. A., Hernández-Callejo, L., Alonso-Gómez, V., Velázquez, N., López-Zavala, R., Acuña, A., & Mariano-Hernández, D. (2020). Techno-economic analysis of hybrid PV/T systems under different climate scenarios and energy tariffs. Solar Energy, 212, 191-202. doi:https://doi.org/10.1016/j.solener.2020.10.079
Shah, H. H., Bareschino, P., Mancusi, E., & Pepe, F. (2023). Environmental Life Cycle Analysis and Energy Payback Period Evaluation of Solar PV Systems: The Case of Pakistan. Energies, 16(17), 6400. doi:https://doi.org/10.3390/en16176400
Georgopoulou, E., Mirasgedis, S., Sarafidis, Y., Giannakopoulos, C., Varotsos, K. V., & Gakis, N. (2024). Climate Change Impacts on the Energy System of a Climate-Vulnerable Mediterranean Country (Greece). Atmosphere, 15(3), 286. doi:https://doi.org/10.3390/atmos15030286
Kany, M. S., Mathiesen, B. V., Skov, I. R., Korberg, A. D., Thellufsen, J. Z., Lund, H., . . . Chang, M. (2022). Energy efficient decarbonisation strategy for the Danish transport sector by 2045. Smart Energy, 5, 100063. doi:https://doi.org/10.1016/j.segy.2022.100063
Nwokolo, S., Eyime, E., Obiwulu, A., & Ogbulezie, J. (2023). Exploring Cutting-Edge Approaches to Reduce Africa's Carbon Footprint through Innovative Technology Dissemination. Trends in Renewable Energy, 10(1), 1-29. doi:http://dx.doi.org/10.17737/tre.2024.10.1.00163
Nwokolo, S. C., Singh, R., Khan, S., Kumar, A., & Luthra, S. (2023). Africa’s Awakening to Climate Action. In Africa's Path to Net-Zero: Exploring Scenarios for a Sustainable Energy Transition (pp. 299-310). Cham: Springer Nature Switzerland. doi:https://doi.org/10.1007/978-3-031-44514-9_9
Nwokolo, S. C., Singh, R., Khan, S., Kumar, A., & Luthra, S. (2023). Influencing the Scale of Africa’s Energy Transition. In Africa's Path to Net-Zero: Exploring Scenarios for a Sustainable Energy Transition (pp. 75-91). Cham: Springer Nature Switzerland. doi:https://doi.org/10.1007/978-3-031-44514-9_4
Nwokolo, S. C., Singh, R., Khan, S., Kumar, A., & Luthra, S. (2023). Remedies to the Challenges of Renewable Energy Deployment in Africa. In Africa's Path to Net-Zero: Exploring Scenarios for a Sustainable Energy Transition (pp. 59-74). Cham: Springer Nature Switzerland. doi:https://doi.org/10.1007/978-3-031-44514-9_3
Nwokolo, S. C., Singh, R., Khan, S., Kumar, A., & Luthra, S. (2023). Introduction: Africa’s Net Zero Transition. In Africa's Path to Net-Zero: Exploring Scenarios for a Sustainable Energy Transition (pp. 1-13). Cham: Springer Nature Switzerland. doi:https://doi.org/10.1007/978-3-031-44514-9_1
Agbor, M., Udo, S., Ewona, I., Nwokolo, S., Ogbulezie, J., Amadi, S., & Billy, U. (2023). Effects of Angstrom-Prescott and Hargreaves-Samani Coefficients on Climate Forcing and Solar PV Technology Selection in West Africa. Trends in Renewable Energy, 9(1), 78-106. doi:http://dx.doi.org/10.17737/tre.2023.9.1.00150
Agbor, M. E., Udo, S. O., Ewona, I. O., Nwokolo, S. C., Ogbulezie, J. C., & Amadi, S. O. (2023). Potential impacts of climate change on global solar radiation and PV output using the CMIP6 model in West Africa. Cleaner Engineering and Technology, 13, 100630. doi:https://doi.org/10.1016/j.clet.2023.100630
Benatallah, M., Bailek, N., Bouchouicha, K., Sharifi, A., Abdel-Hadi, Y., Nwokolo, S. C., ... & M. El-kenawy, E. S. (2024). Solar Radiation Prediction in Adrar, Algeria: A Case Study of Hybrid Extreme Machine-Based Techniques. International Journal of Engineering Research in Africa, 68, 151-164. doi:https://doi.org/10.4028/p-VH0u4y
International Energy Agency (IEA). (2020). World Energy Model Documentation 2020 Version. https://iea.blob.core.windows.net/assets/fa87681d-73bd-4719-b1e5-69670512b614/WEM_Documentation_WEO2020.pdf (accessed on 11/14/2024)
Nwokolo, S. C., Obiwulu, A. U., & Ogbulezie, J. C. (2023). Machine learning and analytical model hybridization to assess the impact of climate change on solar PV energy production. Physics and Chemistry of the Earth, Parts A/B/C, 130, 103389. doi:https://doi.org/10.1016/j.pce.2023.103389
International Energy Agency (IEA). (2021), The Role of Critical Minerals in Clean Energy Transitions, IEA, Paris https://www.iea.org/reports/the-role-of-critical-minerals-in-clean-energy-transitions (accessed on 11/14/2024)
Liang, Y., Kleijn, R., & van der Voet, E. (2023). Increase in demand for critical materials under IEA Net-Zero emission by 2050 scenario. Applied Energy, 346, 121400. doi:https://doi.org/10.1016/j.apenergy.2023.121400
Khurshid, A., Khan, K., & Cifuentes-Faura, J. (2023). 2030 Agenda of sustainable transport: Can current progress lead towards carbon neutrality? Transportation Research Part D: Transport and Environment, 122, 103869. doi:https://doi.org/10.1016/j.trd.2023.103869
Khurshid, A., Khan, K., Chen, Y., & Cifuentes-Faura, J. (2023). Do green transport and mitigation technologies drive OECD countries to sustainable path? Transportation Research Part D: Transport and Environment, 118, 103669. doi:https://doi.org/10.1016/j.trd.2023.103669
Khurshid, A., Rauf, A., Qayyum, S., Calin, A. C., & Duan, W. (2023). Green innovation and carbon emissions: the role of carbon pricing and environmental policies in attaining sustainable development targets of carbon mitigation—evidence from Central-Eastern Europe. Environment, Development and Sustainability, 25(8), 8777-8798. doi:https://doi.org/10.1007/s10668-022-02422-3
Xia, X., Li, P., Xia, Z., Wu, R., & Cheng, Y. (2022). Life cycle carbon footprint of electric vehicles in different countries: A review. Separation and Purification Technology, 301, 122063. doi:https://doi.org/10.1016/j.seppur.2022.122063
Liu, X., Razzaq, A., Shahzad, M., & Irfan, M. (2022). Technological changes, financial development and ecological consequences: A comparative study of developed and developing economies. Technological Forecasting and Social Change, 184, 122004. doi:https://doi.org/10.1016/j.techfore.2022.122004
Huang, L., Krigsvoll, G., Johansen, F., Liu, Y., & Zhang, X. (2018). Carbon emission of global construction sector. Renewable and Sustainable Energy Reviews, 81, 1906-1916. doi:https://doi.org/10.1016/j.rser.2017.06.001
International Energy Agency. (2019). Africa Energy Outlook 2019. https://www.iea.org/reports/africa-energy-outlook-2019 (accessed on 10/29/2024)
Nwokolo, S. C., Meyer, E. L., & Ahia, C. C. (2024). Exploring the Interactive Influences of Climate Change and Urban Development on the Fraction of Absorbed Photosynthetically Active Radiation. Atmosphere, 15(3), 253. doi:https://doi.org/10.3390/atmos15030253
Nwokolo, S. C., Proutsos, N., Meyer, E. L., & Ahia, C. C. (2023). Machine learning and physics-based hybridization models for evaluation of the effects of climate change and urban expansion on photosynthetically active radiation. Atmosphere, 14(4), 687. doi:https://doi.org/10.3390/atmos14040687
Nwokolo, S., Obiwulu, A., Amadi, S., & Ogbulezie, J. (2023). Assessing the Impact of Soiling, Tilt Angle, and Solar Radiation on the Performance of Solar PV Systems. Trends in Renewable Energy, 9(2), 120-136. doi:http://dx.doi.org/10.17737/tre.2023.9.2.00156
Qiao, Q., Eskandari, H., Saadatmand, H., & Sahraei, M. A. (2024). An interpretable multi-stage forecasting framework for energy consumption and CO2 emissions for the transportation sector. Energy, 286, 129499. doi:https://doi.org/10.1016/j.energy.2023.129499
IEA. (2021). World Energy Outlook 2021, IEA, Paris https://www.iea.org/reports/world-energy-outlook-2021 (accessed on 10/30/2024)
Emami Javanmard, M., Tang, Y., Wang, Z., & Tontiwachwuthikul, P. (2023). Forecast energy demand, CO2 emissions and energy resource impacts for the transportation sector. Applied Energy, 338, 120830. doi:https://doi.org/10.1016/j.apenergy.2023.120830
Giannakis, E., Serghides, D., Dimitriou, S., & Zittis, G. (2020). Land transport CO2 emissions and climate change: evidence from Cyprus. International Journal of Sustainable Energy, 39(7), 634–647. doi://doi.org/10.1080/14786451.2020.1743704
Sahraei, M. A., Duman, H., Çodur, M. Y., & Eyduran, E. (2021). Prediction of transportation energy demand: Multivariate Adaptive Regression Splines. Energy, 224, 120090. doi:https://doi.org/10.1016/j.energy.2021.120090
Sahraei, M. A., & Çodur, M. K. (2022). Prediction of transportation energy demand by novel hybrid meta-heuristic ANN. Energy, 249, 123735. doi:https://doi.org/10.1016/j.energy.2022.123735
Çodur, M. Y., & Ünal, A. (2019). An Estimation of Transport Energy Demand in Turkey via Artificial Neural Networks. Promet - Traffic&Transportation, 31(2), 151-161. doi:https://doi.org/10.7307/ptt.v31i2.3041
Hoxha, J., Çodur, M. Y., Mustafaraj, E., Kanj, H., & El Masri, A. (2023). Prediction of transportation energy demand in Türkiye using stacking ensemble models: Methodology and comparative analysis. Applied Energy, 350, 121765. doi:https://doi.org/10.1016/j.apenergy.2023.121765
Awodele, I. A., Mewomo, M. C., Municio, A. M. G., Chan, A. P. C., Darko, A., Taiwo, R., Olatunde, N. A., Eze, E. C., & Awodele, O. A. (2024). Awareness, adoption readiness and challenges of railway 4.0 technologies in a developing economy. Heliyon, 10(4). doi:https://doi.org/10.1016/j.heliyon.2024.e25934
Chen, Z., & Su, S.-I. I. (2014). Photovoltaic supply chain coordination with strategic consumers in China. Renewable Energy, 68, 236-244. doi:https://doi.org/10.1016/j.renene.2014.01.035
International Energy Agency (IEA). (2022). Africa energy outlook 2022. In World Energy Outlook 2022. https://www.iea.org/reports/africa-energy-outlook-2022 (accessed on 10/28/2024)
International Energy Agency (IEA). (2021). World Energy Outlook 2021, IEA, Paris https://www.iea.org/reports/world-energy-outlook-2021 (accessed on 10/30/2024)
International Energy Agency (IEA). (2021). Net Zero by 2050, IEA, Paris https://www.iea.org/reports/net-zero-by-2050 (accessed on 10/30/2024)
International Energy Agency (IEA). (2021). The Role of Critical Minerals in Clean Energy Transitions, IEA, Paris https://www.iea.org/reports/the-role-of-critical-minerals-in-clean-energy-transitions (accessed on 11/15/2024)
Nwokolo, S. C., Singh, R., Khan, S., & Kumar, A. (2025). Chapter 12 - Final word: African nations urged to reassess rapid adoption of leapfrogging strategies proposed by advanced nations. In S. C. Nwokolo, R. Singh, S. Khan, & A. Kumar (Eds.), Technological Pathways for Africa' s Net-Zero Economy (pp. 449-472): Elsevier. doi:https://doi.org/10.1016/B978-0-443-31486-5.00012-4
Nwokolo, S. C., Singh, R., Khan, S., & Kumar, A. (2025). Chapter 10 - Harnessing industry 4.0 for Africa’s net zero economy through technological pathways. In S. C. Nwokolo, R. Singh, S. Khan, & A. Kumar (Eds.), Technological Pathways for Africa' s Net-Zero Economy (pp. 249-282): Elsevier. doi:https://doi.org/10.1016/B978-0-443-31486-5.00010-0
Nwokolo, S. C., Singh, R., Khan, S., & Kumar, A. (2025). Chapter 9 - Net zero technology and circular economy. In S. C. Nwokolo, R. Singh, S. Khan, & A. Kumar (Eds.), Technological Pathways for Africa' s Net-Zero Economy (pp. 237-247): Elsevier. doi:https://doi.org/10.1016/B978-0-443-31486-5.00009-4
Nwokolo, S. C., Singh, R., Khan, S., & Kumar, A. (2025). Chapter 8 - Key components of net zero technology. In S. C. Nwokolo, R. Singh, S. Khan, & A. Kumar (Eds.), Technological Pathways for Africa' s Net-Zero Economy (pp. 217-235): Elsevier. doi:https://doi.org/10.1016/B978-0-443-31486-5.00008-2
Nwokolo, S. C., Singh, R., Khan, S., & Kumar, A. (2025). Chapter 7 - Key players in net zero technology. In S. C. Nwokolo, R. Singh, S. Khan, & A. Kumar (Eds.), Technological Pathways for Africa' s Net-Zero Economy (pp. 193-215): Elsevier. doi:https://doi.org/10.1016/B978-0-443-31486-5.00007-0
Nwokolo, S. C., Singh, R., Khan, S., & Kumar, A. (2025). Chapter 6 - Role of digitalization and connectivity for achieving a net zero economy in Africa. In S. C. Nwokolo, R. Singh, S. Khan, & A. Kumar (Eds.), Technological Pathways for Africa' s Net-Zero Economy (pp. 175-192): Elsevier. doi:https://doi.org/10.1016/B978-0-443-31486-5.00006-9
Nwokolo, S. C., Singh, R., Khan, S., & Kumar, A. (2025). Chapter 5 - International assistance for Africa's net zero technology in Africa. In S. C. Nwokolo, R. Singh, S. Khan, & A. Kumar (Eds.), Technological Pathways for Africa' s Net-Zero Economy (pp. 159-174): Elsevier. doi:https://doi.org/10.1016/B978-0-443-31486-5.00005-7
Nwokolo, S. C., Singh, R., Khan, S., & Kumar, A. (2025). Chapter 3 - Current state of energy in Africa. In S. C. Nwokolo, R. Singh, S. Khan, & A. Kumar (Eds.), Technological Pathways for Africa' s Net-Zero Economy (pp. 77-137): Elsevier. doi:https://doi.org/10.1016/B978-0-443-31486-5.00003-3
Nwokolo, S. C., Singh, R., Khan, S., & Kumar, A. (2024). Technological Pathways for Africa' s Net-Zero Economy: Technology Solutions to Unlock Africa’s Sustainable Future. Elsevier Science. doi:https://doi.org/10.1016/C2023-0-52499-1
Nwokolo, S. C., Eyime, E. E., Obiwulu, A. U., Meyer, E. L., Ahia, C. C., Ogbulezie, J. C., & Proutsos, N. (2024). A multi-model approach based on CARIMA-SARIMA-GPM for assessing the impacts of climate change on concentrated photovoltaic (CPV) potential. Physics and Chemistry of the Earth, Parts A/B/C, 134, 103560. doi:https://doi.org/10.1016/j.pce.2024.103560
Zeng, S., Li, G., Wu, S., & Dong, Z. (2022). The impact of green technology innovation on carbon emissions in the context of carbon neutrality in China: Evidence from spatial spillover and nonlinear effect analysis. International Journal of Environmental Research and Public Health, 19(2), 730. doi:https://doi.org/10.3390/ijerph19020730
Rezaei, M. H., Sadeghzadeh, M., Alhuyi Nazari, M., Ahmadi, M. H., & Astaraei, F. R. (2018). Applying GMDH artificial neural network in modeling CO2 emissions in four nordic countries. International Journal of Low-Carbon Technologies, 13(3), 266-271. doi:https://doi.org/10.1093/ijlct/cty026
Tóth-Nagy, C., Conley, J. J., Jarrett, R. P., & Clark, N. N. (2006). Further Validation of Artificial Neural Network-Based Emissions Simulation Models for Conventional and Hybrid Electric Vehicles. Journal of the Air & Waste Management Association, 56(7), 898–910. doi:https://doi.org/10.1080/10473289.2006.10464513
Öztürk, O. B., & Başar, E. (2022). Multiple linear regression analysis and artificial neural networks based decision support system for energy efficiency in shipping. Ocean Engineering, 243, 110209. doi:https://doi.org/10.1016/j.oceaneng.2021.110209
Ofosu-Adarkwa, J., Xie, N., & Javed, S. A. (2020). Forecasting CO2 emissions of China's cement industry using a hybrid Verhulst-GM(1,N) model and emissions' technical conversion. Renewable and Sustainable Energy Reviews, 130, 109945. doi:https://doi.org/10.1016/j.rser.2020.109945
Natarajan, Y., Wadhwa, G., Sri Preethaa, K. R., & Paul, A. (2023). Forecasting carbon dioxide emissions of light-duty vehicles with different machine learning algorithms. Electronics, 12(10), 2288. doi:https://doi.org/10.3390/electronics12102288
International Renewable Energy Agency (IRNEA). (2022). Renewable Power Generation Costs in 2021. https://www.irena.org/publications/2022/Jul/Renewable-Power-Generation-Costs-in-2021 (accessed on 10/28/2024)
Maaouane, M., Chennaif, M., Zouggar, S., Krajačić, G., Duić, N., Zahboune, H., & Kerkour ElMiad, A. (2022). Using neural network modelling for estimation and forecasting of transport sector energy demand in developing countries. Energy Conversion and Management, 258, 115556. doi:https://doi.org/10.1016/j.enconman.2022.115556
Nwokolo, S. C., Singh, R., Khan, S., Kumar, A., & Luthra, S. (2023). Africa’s Awakening to Climate Action. In Africa's Path to Net-Zero: Exploring Scenarios for a Sustainable Energy Transition (pp. 299-310). Cham: Springer Nature Switzerland. doi:https://doi.org/10.1007/978-3-031-44514-9_9
Nwokolo, S. C., Singh, R., Khan, S., Kumar, A., & Luthra, S. (2023). Introduction: Africa’s Net Zero Transition. In Africa's Path to Net-Zero: Exploring Scenarios for a Sustainable Energy Transition (pp. 1-13). Cham: Springer Nature Switzerland. doi:https://doi.org/10.1007/978-3-031-44514-9_1
Nwokolo, S. C., Singh, R., Khan, S., Kumar, A., & Luthra, S. (2023). Scenarios that Could Give Rise to an African Net-Zero Energy Transition. In Africa's Path to Net-Zero: Exploring Scenarios for a Sustainable Energy Transition (pp. 263-298). Cham: Springer Nature Switzerland. doi: https://doi.org/10.1007/978-3-031-44514-9_8
Obiwulu, A. U., Erusiafe, N., Olopade, M. A., & Nwokolo, S. C. (2022). Modeling and estimation of the optimal tilt angle, maximum incident solar radiation, and global radiation index of the photovoltaic system. Heliyon, 8(6). doi:https://doi.org/10.1016/j.heliyon.2022.e09598
Benatallah, M., Bailek, N., Bouchouicha, K., Sharifi, A., Abdel-Hadi, Y., Nwokolo, S. C., ... & M. El-kenawy, E. S. (2024). Solar Radiation Prediction in Adrar, Algeria: A Case Study of Hybrid Extreme Machine-Based Techniques. International Journal of Engineering Research in Africa, 68, 151-164. doi:https://doi.org/10.4028/p-VH0u4y
Hassan, M. A., Bailek, N., Bouchouicha, K., Ibrahim, A., Jamil, B., Kuriqi, A., ... & El-kenawy, E. S. M. (2022). Evaluation of energy extraction of PV systems affected by environmental factors under real outdoor conditions. Theoretical and Applied Climatology, 150(1), 715-729. doi:https://doi.org/10.1007/s00704-022-04166-6
Obiwulu, A. U., Chendo, M. A. C., Erusiafe, N., & Nwokolo, S. C. (2020). Implicit meteorological parameter-based empirical models for estimating back temperature solar modules under varying tilt-angles in Lagos, Nigeria. Renewable Energy, 145, 442-457. doi:https://doi.org/10.1016/j.renene.2019.05.136
Nwokolo, S. C., Ogbulezie, J. C., & Umunnakwe Obiwulu, A. (2022). Impacts of climate change and meteo-solar parameters on photosynthetically active radiation prediction using hybrid machine learning with Physics-based models. Advances in Space Research, 70(11), 3614-3637. doi:https://doi.org/10.1016/j.asr.2022.08.010
Nwokolo, S. C., Ogbulezie, J. C., & Ushie, O. J. (2023). A multi-model ensemble-based CMIP6 assessment of future solar radiation and PV potential under various climate warming scenarios. Optik, 285, 170956. doi:https://doi.org/10.1016/j.ijleo.2023.170956
Le Cornec, C. M. A., Molden, N., van Reeuwijk, M., & Stettler, M. E. J. (2020). Modelling of instantaneous emissions from diesel vehicles with a special focus on NOx: Insights from machine learning techniques. Science of The Total Environment, 737, 139625. doi:https://doi.org/10.1016/j.scitotenv.2020.139625
Elassy, M., Al-Hattab, M., Takruri, M., & Badawi, S. (2024). Intelligent transportation systems for sustainable smart cities. Transportation Engineering, 16, 100252. doi:https://doi.org/10.1016/j.treng.2024.100252
Nwokolo, S. C. (2017). A comprehensive review of empirical models for estimating global solar radiation in Africa. Renewable and Sustainable Energy Reviews, 78, 955-995. doi:https://doi.org/10.1016/j.rser.2017.04.101
Nwokolo, S. C., & Ogbulezie, J. C. (2018). A qualitative review of empirical models for estimating diffuse solar radiation from experimental data in Africa. Renewable and Sustainable Energy Reviews, 92, 353-393. doi:https://doi.org/10.1016/j.rser.2018.04.118
Nwokolo, S. C., & Ogbulezie, J. C. (2018). A quantitative review and classification of empirical models for predicting global solar radiation in West Africa. Beni-Suef University Journal of Basic and Applied Sciences, 7(4), 367-396. doi:https://doi.org/10.1016/j.bjbas.2017.05.001
Nwokolo, S., & Otse, C. (2019). Impact of Sunshine Duration and Clearness Index on Diffuse Solar Radiation Estimation in Mountainous Climate. Trends in Renewable Energy, 5(3), 307-332. doi:http://dx.doi.org/10.17737/tre.2019.5.3.00107
Huertas-Tato, J., Aler, R., Galván, I. M., Rodríguez-Benítez, F. J., Arbizu-Barrena, C., & Pozo-Vázquez, D. (2020). A short-term solar radiation forecasting system for the Iberian Peninsula. Part 2: Model blending approaches based on machine learning. Solar Energy, 195, 685-696. doi:https://doi.org/10.1016/j.solener.2019.11.091
Ji, Z., Song, H., Lei, L., Sheng, M., Guo, K., & Zhang, S. (2024). A Novel Approach for Predicting Anthropogenic CO2 Emissions Using Machine Learning Based on Clustering of the CO2 Concentration. Atmosphere, 15(3), 323. doi:https://doi.org/10.3390/atmos15030323
Obiwulu, A. U., Erusiafe, N., Olopade, M. A., & Nwokolo, S. C. (2020). Modeling and optimization of back temperature models of mono-crystalline silicon modules with special focus on the effect of meteorological and geographical parameters on PV performance. Renewable Energy, 154, 404-431. doi:https://doi.org/10.1016/j.renene.2020.02.103
Nwokolo, S. C., Obiwulu, A. U., Ogbulezie, J. C., & Amadi, S. O. (2022). Hybridization of statistical machine learning and numerical models for improving beam, diffuse and global solar radiation prediction. Cleaner Engineering and Technology, 9, 100529. doi:https://doi.org/10.1016/j.clet.2022.100529
Bosah, C. P., Li, S., Mulashani, A. K., & Ampofo, G. K. M. (2024). Analysis and forecast of China's carbon emission: evidence from generalized group method of data handling (g-GMDH) neural network. International journal of environmental science and technology, 21(2), 1467-1480. doi:https://doi.org/10.1007/s13762-023-05043-z
Chigora, F., Thabani, N., & Mutambara, E. (2019). Forecasting CO2 Emission for Zimbabwe’s Tourism Destination vibrancy: A Univariate Approach using Box-Jenkins ARIMA Model. African Journal of Hospitality, Tourism and Leisure, 8, 1-15.
Çınarer, G., Yeşilyurt, M. K., Ağbulut, Ü., Yılbaşı, Z., & Kılıç, K. (2024). Application of various machine learning algorithms in view of predicting the CO2 emissions in the transportation sector. Science and Technology for Energy Transition, 79, 15. doi:https://doi.org/10.2516/stet/2024014
Alimo, P. K., Agyeman, S., Agen-Davis, L., Hisseine, M. A., & Sarfo, I. (2024). Lived transportation barriers for persons with disabilities: Contextualizing the Ghana disability law through the lenses of Giddens' theory of structuration. Journal of Transport Geography, 118, 103924. doi:https://doi.org/10.1016/j.jtrangeo.2024.103924
Jain, H. (2024). From pollution to progress: Groundbreaking advances in clean technology unveiled. Innovation and Green Development, 3(2), 100143. doi:https://doi.org/10.1016/j.igd.2024.100143
De Vos, J., Cheng, L., Kamruzzaman, M., & Witlox, F. (2021). The indirect effect of the built environment on travel mode choice: A focus on recent movers. Journal of Transport Geography, 91, 102983. doi:https://doi.org/10.1016/j.jtrangeo.2021.102983
Hassouna, F. M. A., & Al-Sahili, K. (2020). Environmental impact assessment of the transportation sector and hybrid vehicle implications in Palestine. Sustainability, 12(19), 7878. doi:https://doi.org/10.3390/SU12197878
Nwokolo, S. C., Amadi, S. O., Obiwulu, A. U., Ogbulezie, J. C., & Eyibio, E. E. (2022). Prediction of global solar radiation potential for sustainable and cleaner energy generation using improved Angstrom-Prescott and Gumbel probabilistic models. Cleaner Engineering and Technology, 6, 100416. doi:https://doi.org/10.1016/j.clet.2022.100416
Ajayi, O. O., Bagula, A. B., Maluleke, H. C., & Odun-Ayo, I. A. (2021). Transport inequalities and the adoption of intelligent transportation systems in Africa: A research landscape. Sustainability, 13(22), 12891. doi:https://doi.org/10.3390/su132212891
Lv, Z., & Shang, W. (2023). Impacts of intelligent transportation systems on energy conservation and emission reduction of transport systems: A comprehensive review. Green Technologies and Sustainability, 1(1), 100002. doi:https://doi.org/10.1016/j.grets.2022.100002
DOI: http://dx.doi.org/10.17737/tre.2025.11.1.00188
Refbacks
- There are currently no refbacks.
Copyright (c) 2025 Eyime E Eyime, Ogri James Ushie
This work is licensed under a Creative Commons Attribution 4.0 International License.
This work is licensed under a Creative Commons Attribution 4.0 License.Copyright @2014-2025 Trends in Renewable Energy (ISSN: 2376-2136, online ISSN: 2376-2144)