Journal article
Carbon profiles of remote Australian Indigenous communities: A base for opportunities
Energy Policy, Vol.94, pp.77-88
2016
Abstract
A decision-making model was constructed to assist remote Australian Indigenous communities select appropriate climate change mitigation programs. The Resilient Community and Livelihood Asset Integration Model (ReCLAIM) comprises six steps that focus on community assets and aspirations. The second of these steps is to determine the baseline carbon profiles of communities based on six sources of carbon emissions: materials, construction processes, stationary energy, transport, water systems and waste. The methodology employed an annualised lifecycle analysis of housing materials and construction, and an annual inventory of other emission sources. Profiles were calculated for two remote communities and compared to the Australian average and also average electricity consumption by remote communities in the Northern Territory.
The results, expressed in tonnes of carbon dioxide equivalent (tCO(2)-e), showed that average household carbon profiles of the two communities (6.3 and 4.1 tCO(2)-e/capita/yr) were generally lower than the Australian average (7.3 tCO(2)-e/capita/yr). The stationary energy results revealed that infrastructure and building design could raise fuel consumption and costs, and therefore carbon emissions, despite modest lifestyles. The carbon emission categories differed between the two communities highlighting the need for an individualised approach to understanding the drivers of carbon emissions and mitigation responses.
Details
- Title
- Carbon profiles of remote Australian Indigenous communities: A base for opportunities
- Authors/Creators
- J. Stewart (Author/Creator) - Murdoch UniversityM. Anda (Author/Creator) - Murdoch UniversityR.J. Harper (Author/Creator) - Murdoch University
- Publication Details
- Energy Policy, Vol.94, pp.77-88
- Publisher
- Elsevier BV
- Identifiers
- 991005540308907891
- Copyright
- © 2016 Elsevier Ltd.
- Murdoch Affiliation
- School of Engineering and Information Technology; School of Veterinary and Life Sciences
- Language
- English
- Resource Type
- Journal article
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