No abstract

Coastal urban megacities across Asia face significant risks from climate change, including coastal flooding, high temperatures, urban heat island impacts and air pollution. These hazards are associated with negative impacts on infrastructure, communities and the environment. To identify the current intensity of climate change impacts in coastal urban megacities, an integrated evaluation method is needed. Firstly, the present study assesses the climate change impacts of Guangzhou, a Chinese coastal urban megacity, for both physical and social aspects. This study includes 60 years of time-series data for 1960–2020 to examine temperatures, precipitation, humidity and air pollution in Guangzhou city. At the same time, a survey was conducted between April and July 2022 in this megacity and collected the views of 336 people on climate change and its associated environmental impacts. Secondly, the Ganzhou city results are compared with existing data from similar nearby cities to evaluate the diverse climate change trends. Results show that during 1961-1990, the city received the most rainfall in May, reaching 283.6 mm. From 1990 to 2020, June recorded the highest rainfall of 356.6 mm and shows an increase of 73 mm during that period. The very severe monsoon season brought an increased risk of flooding. Results also revealed that the warmest month is July, and the coldest month is January, and both months showed increased temperatures of 0.60℃. Comparison results revealed that Guangzhou is not the only city which scored increased highest temperatures; other nearby cities including Heyuan, Shantou and Shaoguan also scored increased highest temperatures. The survey reveals that the majority of respondents (75%) perceived the increased frequency of extreme weather, including typhoons, heavy rainfall and multiple days of hot weather, such as higher temperatures and an increased number of hot days. In the responses to the questions related to the heat island effect, more than 80% of residents are aware of the existence of the heat island and its impacts. People believe that the primary causes of the urban heat island problem are industrial production and anthropogenic heat generated by the city. These results will be helpful to local and national policy and decision makers to revise and/or develop new strategies to improve the environment and quality of life in coastal megacities, particularly Ganzhou.

The city of Cairo has witnessed a considerable increase in crimes against women, compelling women to avoid or minimise their use of public spaces in recent years. The absence of consideration for women in city planning has made Egyptian women feel further excluded and threatened by the public space, in addition to the patriarchal social relations and religious conservatism. As part of the ‘gender-inclusive cities' research project, this study adopts a participatory approach as a tool for women's empowerment with the goal of promoting bottom-up models of planning, dissolving gendered norms, and improving women's status in a patriarchal society. The chapter provides an example of localised gender-inclusive design addressing women's spatial sensibilities and connecting them to the broader objectives of participation and emancipation. The findings of this study can help planners and policy makers co-create safer public spaces for local women, reduce spatial inequality, and facilitate their right to the city.

The Level of Detail (LoD), a parameter used to define the information contained in building models, is an important factor to consider in modeling building energy at the urban scale. In this research, we conducted a parametric study regarding the data requirements for the estimation of the annual residential heat demand in London. More particularly, the requirement of the observation of the actual roof type (LoD2) and the window-to-wall ratio (LoD3) was examined in two different case study areas. Meanwhile, an adaptive comfort level study was implemented using LoD5 models, and its results were assessed holistically with the heat demand to reveal the energy performance of the buildings. The results showed that there was a minor difference in the upgrade of a lower to higher LoD regarding these parameters. At an urban scale, the energy demand of buildings could be estimated using an assumption of archetypes and building ages. However, with a scalable parametric script developed in places, models with a high LoD could provide more detailed insights in the energy performance assessment without generating excessive workload.

The energy consumption and its related carbon emission of non-domestic complex buildings in an urban context are complicated due to their wide variety of functions and services. A detailed assessment of the carbon emission of such buildings can contribute to decision making for in-operation building management and schematic designs of future proposals. Concurrently, advances in smart meter data analytics and sensor-enabled operational data streams offer the opportunity to investigate this problem at a finer temporal resolution. This research developed a daily carbon emission benchmarking system of a mixed-use building in a UK university. The research period was set at an annual range from 1 January 2019 to 31 December 2019 and was segmented by strategic periods in line with the operation schedule of the building. The daily benchmark revealed the fluctuation of the building’s energy consumption and associated carbon emissions. Based on this, a digital twin framework was developed to identify the possible time periods when the building is less carbon efficient and potential building characters that can lead to increased carbon emission in the operational stage compared with what originally expected at the design stage. We discuss how these insights can offer actionable knowledge for user groups such as asset managers and architects.