A parametric urban design model to optimize life cycle carbon footprint of green open spaces

Leung, T.M.; (2022) A parametric urban design model to optimize life cycle carbon footprint of green open spaces. In: Annual Conference Proceedings of the XXVIII International Seminar on Urban Form. University of Strathclyde Publishing, Glasgow, pp. 424-431. ISBN 9781914241161

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More people live in cities nowadays. In fact, urbanization can pose ecological burdens to our planet. Human activities in urban areas constitute 71 to 76% of global carbon emissions, which is one of the causes of climate change. Research results also suggested that land use patterns and urban morphology can affect carbon emission in cities. Consequently, there is an urgent call to designing cities which can reduce carbon emission. To this end, studies have shown that trees in urban green spaces could help offset carbon emission in cities by carbon sequestration. Although there have been studies on the carbon balance of urban green spaces, few attempts have been made to investigate the optimization of green space design to reduce carbon emissions from cities. In parallel, there is a recent trend to utilizing parametric design models for urban design tasks. Efforts have been put on examining the use of parametric urban design models in optimizing urban design options. Moreover, previous studies suggested it is possible to adopt performance values as parameter input to generate design options. Accordingly, the primary aim of the current study is to develop a parametric urban design model which takes life cycle CO2 sequestration of trees as the parameter input to generate urban green space design options in the early design stage. A case study will be conducted to illustrate how the model can be developed. The Rhino3D plugin Grasshopper will be used to develop the parametric design model. Space Syntax measure intelligibility will also be included in the model. Life cycle CO2 sequestration of the open space can be optimized against the intelligibility of the space by using the model.

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