In the recent past, machine learning (ML) techniques such as artificial neural networks (ANN) have been increasingly used to model algal bloom dynamics. In the present paper, along with ANN, we select genetic programming (GP) for modelling and prediction of algal blooms in Tolo Harbour, Hong Kong. The study of the weights of the trained ANN and also the GP-evolved equations shows that they correctly identify the ecologically significant variables. Analysis of various ANN and GP scenarios indicates that good predictions of long-term trends in algal biomass can be obtained using only chlorophyll-a as input. The results indicate that the use of biweekly data can simulate long-term trends of algal biomass reasonably well, but it is not ideally suited to give short-term algal bloom predictions.

Research on urban heat mitigation has been growing in recent years with many of the studies focusing on green infrastructure (GI) as a strategy to mitigate the adverse effects of an urban heat island (UHI). This paper aims at presenting a review of the range of findings from GI research for urban heat mitigation through a review of scientific articles published during the years 2009–2020. This research includes a review of the different types of GI and its contribution for urban heat mitigation and human thermal comfort. In addition to analysing different mitigation strategies, numerical simulation tools that are commonly used are also reviewed. It is seen that ENVI-met is one of the modelling tools that is considered as a reliable to simulate different mitigation strategies and hence has been widely used in the recent past. Considering its popularity in urban microclimate studies, this article also provides a review of ENVI-met simulation results that were reported in the reviewed papers. It was observed that the majority of the research was conducted on a limited spatial scale and focused on temperature and human thermal comfort.

The globe is at a crossroads in terms of the urban heat island effect, with rising surface temperatures due to urbanization and an expanding built environment. This cause-and-effect connection may be linked to weather-related dangers, natural disasters, and disease outbreaks. Urbanization and industrialization will not lead to a secure and sustainable future. Finding solutions to problems such as the heat island effect is at the forefront of scientific research and policy development. Sustainable ways to decrease urban heat island impacts are a core principle for urban planners. This literature study examines the benefits of adding green infrastructure and sustainable materials in built-up areas to reduce the urban heat island effect. Materials such as reflective street pavements, coating materials including light-colored paint, phase-change materials, color-changing paint, fluorescence paint, and energy-efficient appliances are considered sustainable materials, whereas green infrastructure like green roofs, green walls, green parking and pavements, and shaded streets are considered to mitigate the urban heat island effect. The hurdles to the widespread adoption of such practices include a lack of governmental legislation, insufficient technological development, an erroneous estimation of economic gains, and unwillingness on the part of impacted parties.