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Africa's urbanization rate has quadrupled from 14% in 1950 to about 44% in 2022. A variety of urban growth models have been used to measure and monitor urbanization, its drivers and implications for urban planning and sustainability. This paper reviews the performance of various Cellular Automata (CA)-based urban growth models and their implications for the urbanization processes in Africa. To this end, we employ a systematic review approach to identify the final 18 articles published in Web of Science-indexed journals until 2022. Our review found that the CA-based urban growth model has been successfully used in Africa to track the impacts of urban growth, assess different city growth scenarios and compare the performance of various CA-integrated models. Yet, most of the reviewed CA-based studies have focused on more urbanized regions of the continent. The result also reveals that integrating the CA model with other statistical methods improves its broader application and practicality than a conventional CA model. Our findings give planners, policymakers, and other urban stakeholders a more in-depth understanding of the challenges of unplanned urbanization and the need for meaningful participation from urban stakeholders in city growth and sustainable land use management that balances urban growth and the environment. [ABSTRACT FROM AUTHOR]

This research paper proposes a novel multi-model approach, integrating the CARIMA-SARIMA-GPM framework, to assess the combined impacts of climate change and land use change on the potential of concentrated photovoltaic (CPV) systems. By considering both climatic variables and land use patterns, this study aims to provide a comprehensive understanding of how these factors influence CPV performance in the context of a changing environment. The proposed methodology offers valuable insights into the future viability and sustainability of CPV technology, enabling informed decision-making for policymakers, energy planners, and investors in the Middle East and Africa. As a result, the ability of the hybrid evolutionary CARIMA-SARIMA-GPM to predict the potential of CPV energy output for assessing the impacts of climate change on it was investigated in Alice Springs, the Middle East, and Africa. The outcome showed that the hybrid model significantly outperformed the other machine learning approaches. The fitted model was used to assess the potential impacts of climate change on CPV generation in Alice Springs, Australia, as well as the Middle East's and Africa's comparable climatic conditions. According to the study, climate change had the greatest impact on solar CPV energy production in Alice Springs, where it decreased the most by 8.577% under moderate forcing scenarios (SSP245) during the boreal summer season; moderately in the Middle East, where it decreased the mode by 2.316% under mitigation scenarios (SSP126) during the boreal summer season; and extremely minimally in Africa, where it decreased the mode by 1.263% under the far future sequencing period (2051–2099). Climate change also increased solar CPV energy production significantly in the Middle East in the far future sequencing period (2051–2099), as well as in Alice Springs, Australia, and Africa in the near future sequencing period (2015–2050). The strongest forcing scenario (SSP585) increased by 7.644% during the boreal autumn season in Africa; moderately increased by 6.502% during the boreal spring season in the Middle East; and had the least beneficial effects in Alice Springs, Australia, with increases of 5.538% during the boreal winter season. On an annual basis, all three regions showed a similar trend. Climate change (CLC) and urban expansion (URE) were also investigated in the Middle East and Africa for their effects on changes in solar CPV energy output. URE had a greater impact in Africa than the Middle East under the effective scenario, with a URE value of 45.45% for Africa and 20.15% for the Middle East, whereas CLC had a greater impact in the Middle East than Africa, with a CLC value of 29.01% compared to 5.47% for Africa. CLC and CPV residual factors, on the other hand, have a greater impact in the Middle East than in Africa, with effects of 29.01% and 50.83%, respectively, compared to 5.47% and 49.09%. The potential difference that drives the remediation of specific pollutants lies in the application of advanced technologies and sustainable practices. By exploring innovative solutions, such as using renewable energy sources like concentrated photovoltaic (CPV) systems, we can effectively mitigate the impacts of climate change and land use changes on pollutant concentrations. These technologies have the potential to significantly reduce pollution levels and create a cleaner and healthier environment for future generations. Assessing the CPV potential in different regions like Alice Springs, Australia, the Middle East, and Africa allows us to identify areas with high solar energy resources that can be harnessed for efficient pollutant remediation. Implementing prompt climate mitigation and adaptation measures is crucial for achieving a net-zero energy transition in the Middle East and Africa by 2050. In this context, prioritizing solar energy as the primary source of renewable energy is imperative for successful low-carbon economic planning in these regions. • CARIMA-SARIMA-GPM outperforms other applicable models • By 2100, the CPV potential in Alice Springs could increase by 0.082–5.338% at 1.5 °C • By 2100, the Middle East's CPV potential could increase by 0.021–0.221% at 1.5 °C. • By 2100, Africa's CPV potential could increase by 0.133–7.644% at 1.5 °C. • Climate change has harmed Alice Springs and the Middle East more than Africa. [ABSTRACT FROM AUTHOR]