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The performance of thermal comfort utilising machine learning and its acceptability by students and other users at the Professor Sir Edouard Lim Fat Engineering Tower at the University of Mauritius are evaluated in this study. Students and building occupants were asked to fill out surveys on-site as data was gathered from sensors throughout the structure. The Thermal Sensation Vote (TSV) and other important data were collected through the surveys, including the effect of wind on thermal comfort. An adaptive model incorporating solar and wind effects was evaluated using multiple linear regression techniques and RStudio. Three models were used to evaluate thermal comfort, including the adaptive one. Numerous models were compared and evaluated in order to select the best one. It was found that the adaptive model (Model 1) was deemed to be the best model for its application. It was also found that Fanger's PMV/PPD (Model 2) was a very good approach to determining thermal comfort. Through thorough analysis, it was concluded that the range of air temperature and wind speed for thermal comfort was 25.830°C–28.0°C and 0.26 m/s to 0.42 m/s, respectively. In order for cities to remain secure, resilient and sustainable, it will be important to manage thermal comfort and reduce populations' exposure to heat stress (SDG 11). The achievement of income and productivity goals will be hampered if measures to protect populations from heat stress are not taken (SDG 8). Thermal regulation is also necessary for the provision of numerous health services (SDG 3).

The need to design buildings with due consideration for bioclimatic and passive design is central to promoting sustainability in the built environment from an energy perspective. Indeed, the energy and atmosphere considerations in building design, construction and operation have received the highest consideration in green building frameworks such as LEED and BREEAM to promote SDG 9: Industry, Innovation and Infrastructure and SDG 11: Sustainable Cities and Communities and contributing directly to support SDG 13: Climate Action. The research literature is rich of findings on the efficacy of passive measures in different climate contexts, but given that these measures are highly dependent on the prevailing weather conditions, which is constantly in evolution, disturbed by the climate change phenomenon, there is pressing need to be able to accurately predict such changes in the short (to the minute) and medium (to the hour and day) terms, where AI algorithms can be effectively applied. The dynamics of the weather patterns over seasons, but more crucially over a given season means that optimum response of building envelope elements, specifically through the passive elements, can be reaped if these passive measures can be adapted according to the ambient weather conditions. The use of representative mechatronics systems to intelligently control certain passive measures is presented, together with the potential use of artificial intelligence (AI) algorithms to capture the complex building physics involved to predict the expected effect of weather conditions on the indoor environmental conditions.

In this chapter the potential to use water-based Trombe walls to provide heated water for building applications during the summer months is investigated. Design Builder software is used to model a simple single-story building with a south-facing Trombe wall. The effects of using different thermal storage mediums within the Trombe wall on building heating loads during the winter and building cooling loads during the summer are modeled. The amount of thermal energy stored and temperature of water within the thermal storage medium during hot weather conditions were also simulated. On a sunny day on Toronto, Canada, the average temperature of the water in a Trombe wall integrated into a single-story building can reach ∼57°C, which is high enough to provide for the main hot water usages in buildings. Furthermore, the amount of water heated is three times greater than that required in an average household in Canada. The results from this work suggest that water-based Trombe walls have great potential to enhance the flexibility and utility of Trombe walls by providing heated water for building applications during summer months, without compromising performance during winter months.

Climate change will affect tourism at several temporal and spatial levels. This chapter focuses on the quantification of effects and the development of strategies to reduce extremes and frequencies as well as thresholds in tourism areas. Knowledge about possibilities for mitigation and adaptation of current and expected climate conditions requires interdisciplinary approaches and solutions. Several examples are presented, including the effects of trees against climate change and extreme events (heat waves), behavior adaptations, urban and regional planning measures, bioclimatic conditions in the Mediterranean and human–biometeorological conditions under climate change conditions, and user-friendly computer tools for the quantification of urban bioclimate conditions.

The chapter discusses the effects of climate change on tourism development in Estonia, Latvia, and Lithuania by combining these countries into a single Eastern Baltic Sea Region. The chapter explores the current situation and investigates the trends that will affect the economic development if the present climate conditions are situated in historical context. The first part discusses how destinations can be better managed if they are informed by the scholarship on ecological modernization and updated by a coevolutionary approach to climate change. This discussion proceeds with an analysis of the impact climate change has on tourism following different scenarios of current and future climate conditions. The development of tourism in the Baltic countries is then assessed with references to sustainable development. Overall the chapter demonstrates how destinations can cope with the changing preferences of tourists even in the face of highly unpredictable climatic developments.

The purpose of this chapter is to address the issue of climate change and its effects on developing insular countries like the Maldives in order to identify adaptive mechanisms and new opportunities in the international context towards achieving sustainable development, taking into account its environmental and social incidences.

Firstly, the chapter introduces some generalities of the Republic of the Maldives and its current challenges. Next, there is a description of the economy of the islands: here the importance of its major source of income, the tourism industry, is highlighted. Then, vulnerabilities and adaptive mechanisms are explored for the particular case of tourism.

Maldivian current efforts in disaster risk management (DRM) mitigation, preparedness, response, and reconstruction stages, and the work between government, private organizations, and civil society, implemented since the 2004 tsunami; and as a response to climate change, are examples of how to apply collaborative approaches proposed by Sustainable Development Objectives, COP21 agreement, and Sendai Framework.

It is difficult to measure the consequences of sustainable development actions by the Maldivian government, especially in the international environment.

The study of the Maldivian DRM strategy in the context of climate change and the lessons from the Maldives’ tourism sector development under climate action serves as a model for other international business organizations which aim to reach sustainable development standards in the Post-2015 Development Agenda.

This chapter evaluated important opportunities for sustainable development agenda that can be learned from DRM measures in Maldives.

The Pacific Island countries are culturally diverse, politically challenging, extremely vulnerable to climate change and natural disaster impacts, and financially heavily dependent on aid flows. This chapter examines barriers and opportunities for Green growth (GG) to flourish in a country with a practically non-existent real economy and which is currently under the threat of disappearance under water. It draws on a visiting experience and lessons from the literature and tries to investigate the role of innovation and entrepreneurship as poles of re-birth and local creativity. More particularly, I here discuss why a least developed country such as Kiribati might be the perfect location for dynamics of GG to get born and how, Kiribati, a country under threat and fear, can be transformed into a lighthouse of entrepreneurship which can give boost to the implementation of one of the most advanced energy technologies in the world. I also discuss how, ultimately, a “least developed economy” can secure scientific lessons, which are highly significant for the international knowledge society.

Due to the more pressing need, the majority of material in this book has dealt with mitigation; interventions to reduce emissions of greenhouse gases (IPCC, 2001) away from a scenario of ‘business as usual’. An early academic review on climate change mitigation and transport appeared in 2007 (Chapman, 2007), a year before the United Kingdom committed itself to the highly ambitious Climate Change Act 2008. The final act sought an ambitious 80% cut in greenhouse gas emissions by 2050. Although criticised in this book as being unrealistic, this is the level of intervention required if ‘dangerous’ climate change is to be avoided (defined as greater than 2°C rise in global temperatures). As Chapter 8 (a policy perspective) explains, such targets, however unrealistic, are informed by considerable input from expert opinion (e.g. Delphi studies) and require a detailed knowledge of current emissions as well as accurate predictions/scenarios of future emissions. For this reason, scenarios and the control of uncertainty were discussed in Chapter 2 towards the start of this book. Indeed, the commonly quoted ‘business as usual’ scenario is in itself too simplistic and highly improbable, not only due to mitigation measures imposed by governments, but also because of the future scarcity of oil which will force change in the medium term regardless. Backcasting is the key tool used to model the continuum of socio-economic scenarios which exist between ‘business as usual’ and the equally unlikely case of all targets being met. However, the science is inherently difficult and the end result is a wide range of permutations and storylines, largely dependent on mitigation. Early progress towards the 80% target has not been promising, but the decarbonisation of the transport sector is still seen as key in meeting the demands of the Climate Change Act 2008. There is a need to tackle the three primary culprits of greenhouse gas emissions in the transport sector: aviation, freight and car ownership (Chapman, 2007). This book has examined in detail how this could be achieved in all these sectors using a range of aspects relating to technological and behavioural change.