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The explosion of data in the information age has provided an opportunity to explore the possibility of characterizing the climate patterns using data mining techniques. Nigeria has a unique tropical climate with two precipitation regimes: low precipitation in the north leading to aridity and desertification and high precipitation in parts of the southwest and southeast leading to large scale flooding. In this research, four indices have been used to characterize the intensity, frequency, and amount of rainfall over Nigeria. A type of Artificial Neural Network called the self-organizing map has been used to reduce the multiplicity of dimensions and produce four unique zones characterizing extreme precipitation conditions in Nigeria. This approach allowed for the assessment of spatial and temporal patterns in extreme precipitation in the last three decades. Precipitation properties in each cluster are discussed. The cluster closest to the Atlantic has high values of precipitation intensity, frequency, and duration, whereas the cluster closest to the Sahara Desert has low values. A significant increasing trend has been observed in the frequency of rainy days at the center of the northern region of Nigeria.

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The growth of cities' population increased the interest in the opportunities and challenges that Information and Communication Technology (ICT) have on carbon footprint reduction, which fosters their environmental sustainability. Using Principal Component Analysis (PCA), six ICT-related variables from European Union (EU) cities were combined into a single twodimensional ICT index. Then, through cluster analysis, cities were clustered into four groups based on the ICT index and Carbon dioxide (CO 2 ) emissions. Using ICT as an indicator of smartness and CO 2 emissions as an indicator of sustainability, we show that it is possible for a city to be smart but not sustainable and vice versa. Results also indicate that there is a gap between cities in northern Europe, which are the top performers in both categories, and cities in south-eastern Europe, which do not perform as well. The need for a common strategy for achieving integrated smart, sustainable and inclusive growth at a European level is demonstrated.

There has been an exponential growth of cities in the last decade. Rural to urban migration are occurring at an unprecedented level. This is partly because cities serve as hubs of innovation offering numerous economic opportunities. However, this growth comes with its unique challenges some of which include strained mobility, pollution, growth of slums etc. The "smart cities" concept aims to address this with increased efficiency using a unique combination of data and technology in every aspect of the city. Even though it is believed that the smart cities concept inherently incorporates sustainability or ultimately leads to a more sustainable city, not all smart city concepts are aligned with sustainability targets. In this research, we provide a more holistic view studying the relationship between a "smart city" and a "sustainable city". We conceptualised a framework to measure the connection between technology and environmental sustainability and categorised European cities based on this relationship. We provide a concise and clearer understanding of the drivers of the use of technology through the sharing economy to foster sustainability in cities by citizens. Using a weighting and meta-analysis of adoption theories, we laid the foundation for additional hypothesises which researchers can evaluate in future smart sustainable cities assessment studies and provided interesting insights for city councils and governments pushing for a citizen adoption of sustainable practices within their administrative boundaries. Lastly, we rank European capital cities based on how smart and sustainable they are using a composite index based on publicly available data. We also carried out a sensitivity analysis and validation study of our results.