Creating LCS Scenarios – The Extended Snapshot (ExSS) Tool
This section explains the procedure and methodology of the Extended Snapshot tool (ExSS) in GHG emissions accounting that informs the design of GHG emission mitigation options for Iskandar Malaysia. ExSS is developed by Kyoto University and the National Institute for Environmental Studies (NIES), Japan, and was first launched in 2006 (Ali et al. 2013). It is a static accounting model with simultaneous equations and the ability to project consistent socio-economic variables, energy demand and supply and CO2 emissions from energy consumption in a particular future year based on a set of future assumptions of development and energy technologies. The tool quantifies economic growth and changes in industrial structure; demography; changes of lifestyles in terms of consumption pattern and energy service demand; transport volume and structure; and low carbon measures that include energy-efficient devices and buildings, renewable energy, modal shift to public transport and fuel mix in power generation (see Gomi et al. 2010).
The methodology for creating LCS scenarios builds on the idea of 'backcasting', which begins with the setting of a desirable LCS goal followed by iterative explorations of possible options to achieve the goal using ExSS. Figure 7.6 summarises the overall process of the method which comprises seven steps.
1. Setting the framework
Framework of an LCS scenario includes a target area, a base year, target year(s), environmental targets and a number of scenarios. The base year provides the base scenario against which the target year scenario is compared. The target year should be far enough to realise the required change and yet near enough to capture with reasonable clarity the development vision and future scenarios in the target area. In the preparation of the LCSBP-IM2025, 2005 is selected as the base year, while the target year of IM's LCS scenario has been set as 2025. For the environmental target, CO2 from energy use is opted for because it is expected to be a main source of GHG emissions in IM in 2025.
2. Descriptions of socio-economic assumptions
Before conducting the quantitative estimation, the qualitative future image of the target area's development is narrated. It is essentially an image of demography,
Fig. 7.6 Creating LCS scenarios, overall process (Source: Gomi et al. 2010, p. 4786)
lifestyle, economy and industry, land use, transportation, technology available, its diffusion level and so on. For the purpose of LCSBP-IM2025, Iskandar Malaysia's Comprehensive Development Plan (CDP) and various State and local official economic and development planning documents have the main sources on which future scenarios of IM are based.
3. Quantification of socio-economic assumptions
To provide 'snapshots' of estimated energy use and GHG emissions based on the future image of IM in Step (2), values of exogenous variables and parameters are set. These are then input into ExSS which then calculates various socio-economic indices of the target year, including population, GDP, output by industry, passenger and freight transport demand.
4. Compilation of low carbon measures
The next step involves the compilation of countermeasures (CM) which are expected to be available in the target year, for example, high-energy-efficiency devices, transport structure change such as public transport, use of renewable energy, energy-saving behaviour and carbon sink. Technical data are required to estimate their effects on reducing GHG emissions. For the purpose of the LCSBP-IM2025, the technical data used have been based on those from a preceding study in Japan's Shiga Prefecture due to limited availability of IM-specific information and, importantly, similarity in the industrial structure and population size of the Shiga and IM regions.
5. Setting introduction of countermeasures
Technological parameters related to energy demand and CO2 emissions, in short energy efficiency, are defined at this stage. Since there can be various portfolios of the measures, it is crucial that appropriate criteria are chosen, for example, cost minimisation, acceptance to stakeholders (through FGDs), realistic levels of technological development and their diffusion rates.
6. Estimation of GHG emission in the target year
Based on the socio-economic indices and assumptions of countermeasures' introduction set in Steps (3) and (5), GHG emissions are finally calculated using ExSS. If the resultant GHG emissions meet the preset reduction target, the correspondent combinations of countermeasures are selected for policy proposal in the next step. Otherwise, Step (5) will be repeated where countermeasures and technological parameters are reset until the GHG reduction target is achieved.
7. Proposal of policies
Policy set to introduce the countermeasures defined is proposed. Available policies depend on the context of the municipality, region or country which they are aimed at addressing. ExSS can calculate emission reduction potential for each countermeasure. Therefore, it can show the reduction potential of measures which especially need to be prioritised. It can also identify measures which have high reduction potential and are therefore important.
