Tooling up urban planning for climate change mitigation in Malaysian cities
The city’s 2-dimensional spatial structure and 3-dimensional form significantly influence its energy and GHG emission intensity. In rapidly developing urban-regions, the ability of the local planning authorities to quantify the spatial structure and form of existing urban areas, new developments and...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
IOP Publishing
2014
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| Subjects: | |
| Online Access: | http://eprints.utm.my/id/eprint/39783/2/1755-1315_18_1_012158.pdf http://eprints.utm.my/id/eprint/39783/ |
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| Summary: | The city’s 2-dimensional spatial structure and 3-dimensional form significantly influence its energy and GHG emission intensity. In rapidly developing urban-regions, the ability of the local planning authorities to quantify the spatial structure and form of existing urban areas, new developments and the emergent urban-region in terms of GHG emission is vital to any effective local, national and global climate change mitigation effort. While a wide array of tools has been developed for assessing built environment sustainability at various spatial scales, these are predominantly eco-efficiency rating tools that do not model the ‘spatial structure-GHG’ relationship and do not illustrate the GHG implications of urban structure and form, which crucially inform local planning decisions with respect to climate change mitigation. This paper takes the first steps in analysing three spatial-based planning models (Envision Tomorrow, GHGProof, URBEMIS) that estimate GHG emissions towards assessing their adaptability for application in Malaysian cities. It looks into the models’ “inner working”, unpacking the variables and their relationships; assumptions and conversion rates used; and their data requirement and structure. The models’ characteristics and features are critically compared to evaluate their capabilities, limitations and relevance to the Malaysian urban planning context, particularly in terms of data availability. |
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