Modelling Microclimates in the Smart City: a Campus Case Study on Natural Ventilation

In recent years, modeling tools have been developed that allow quantifying and comparing the microclimatic impacts of different design options, e.g. modeling wind tunnel effects or surface heat. Our research for open spaces as an essential part of smart cities investigates how landscape architecture designs, e.g. tree planting strategies, green roofs, etc. will interact with the microclimate and natural ventilation or air flow. Addressing open spaces is also an important connecting element across the various disciplines involved and will facilitate close interdisciplinary collaboration. Interdisciplinary collaboration could address the interrelation between outdoor spaces and indoor conditions, public stakeholder involvement, and the risks through extreme weather events. The expected results will inform sustainable landscape design solutions and increase resilience to climate change. We started with a case study in modeling the micro-climate for the new campus masterplan of the University of Sheffield, currently developed by Feilden Clegg Bradley Studios, Grant Associates, & AECOM (2014). Peng & Elwan (2011) had already used ENVI-met to model the impact of climate change on building temperatures; Wong & Jusuf (2008) used GIS. After testing different software packages, we decided to use Autodesk Vasari in comparison, which is well integrated with other Autodesk products. First, past and current wind speeds were collected to calibrate the model. Applying our modelling approach provided figures on how the proposed masterplan design will change the local microclimate on campus and predicted effects on wind speeds on central parts of the campus. The results show that street trees have a significant influence on the air flow and that improved street tree design can increase natural ventilation mitigating the UHI effect on campus. The model also showed some of the interactions between buildings and trees although the used software was rather limited with regard to different vegetation types. The presentation will conclude with suggestions for further research and for future software development to improve the accuracy of microclimate and air flow modeling in smart cities.