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Abstract
This paper contains updated projections for greenhouse gas emissions from stationary energy sources in Australia. The projections were generated using MMRF-Green, a bottom-up CGE model of the economies of Australia’s six states and two territories. MMRF-Green models each region as an economy in its own right, with region-specific prices, region-specific consumers, region-specific industries, and so on. This theoretical structure is supported by a database containing explicit representations of intra-regional, inter-regional and international trade flows, and detailed information on greenhouse gas emissions by fuel, fuel-source, user and user-region. The current MMRF-Green database recognises 52 commodities produced by 46 industries. Of the 52 commodities, 26 are related to energy and transport. There are four primary sources of energy and six refinery products. The refinery products are produced by a single industry. There are six electricity industries and nine transport sectors. For each transport mode, the provision of freight services is treated separately from the provision of passenger services. Each solution of MMRF-Green produces pictures of Australia’s regions at a high level of detail for a particular year. The model can also produce a sequence of annual solutions, linked together by ensuring, for example, that the quantities of opening capital stocks in any year equal the quantities of closing stocks in the previous year. This allows the model to make forecasts at a high level of detail over periods of policy relevance (say up to 10 years). The forecasts of emissions reported in this paper have been made for the Australian Greenhouse Office (AGO), the sponsor of our work. The sponsored work involved the modelling of five scenarios. However, for the sake of brevity, in this paper we focus on just one – the “With measures” case. This scenario includes the impacts of federal and state government measures designed to reduce emissions over the medium term. These measures operate on the supply side (e.g., measures designed to improve the fuel efficiency of coal generation) and on the demand side (e.g., measures designed to improve the electricity efficiency of residential appliances). Careful modelling of these measures is the key to producing believable long-term forecasts for stationary-energy emissions.