A Computational Design Approach for Climate Change Adaptation and UHI Mitigation

Dense urban areas account for more than 80% of global Gross Domestic Product and by 2050 will host around 70% of global population. But while reducing the impact of anthropogenic activities by lowering the emissions deriving from transportation and building energy use and preserving underdeveloped lands, metropolitan areas are facing relevant issues related to their vulnerability to climate and disaster risk, poor human and ecosystems health, and the environmental impact they cause by themselves. Regenerative design strategies - among which Nature-based Solutions (NBS) - play a significant role in climate change adaptation, overall improving the environmental quality of dense urban areas by decreasing greenhouse gas emissions, reducing wellbeing. The potential role of NBS in urban areas depends on several factors, among which weather conditions, urban morphology, and what environmental issue needs to be specifically addressed. A methodology with a specific design tool to select NBS and generate site-specific early-design solutions addressing climate change adaptation is developed. Moreover, a parametric workflow including a computer-aided multi-criteria evaluation tool enables a holistic evaluation of the design solutions and the selection of the most performative ones, depending on Key Performance Indicators. In this sense, the overall goal is to provide designers with advanced tools and analyses to inform their early-stage decisions using an iterative design process, from district to building scale.