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Abstract: Sustainability policies that have quantitative emission or carbon footprint measurements are important in view of climate change and current rapid urbanization in developing countries like Malaysia. Although sustainability policies are mentioned in national development plan as early as in the 1990s, many of these policies are piecemeal and expressed qualitatively. In achieving environmental sustainability, planning of city or a region can be more functional and implementable by using low carbon city concept. Planning a low carbon city uses sustainable development principles; this demonstrates a high level of energy efficiency using low carbon energy sources and production technologies. It also adopts patterns of consumption and behavior that are consistent with low levels of greenhouse gas emissions in the urban areas. The planning of the fast developing region of Iskandar Malaysia, which is located in southern part of Peninsular Malaysia, provides a good opportunity for urban managers to incorporate the ideas of low carbon cities in this proposed high growth urban conurbation. This paper aims to explore implementation of the concept and vision of low carbon scenarios and examine the strategies toward the reduction of CO2 emission. This study also prepares a quantitative scenario study on the establishment of low carbon urban development in Iskandar Malaysia. [Copyright &y& Elsevier]

This study aims to estimate greenhouse gas (GHG) emissions and mitigation potentials in Agriculture, Forestry and Other Land Use (AFOLU) in the Southeast Asian countries: Indonesia, Malaysia and Vietnam, up to 2030. We developed a bottom-up type model named the AFOLUB Model, which calculates GHG mitigations based on the detailed information of specific technologies. The model illustrates producer's behaviour of agricultural production and mitigation technology selection as a result of profit maximization. Using this model, we evaluated mitigations and effective technologies with high mitigation potentials in the sectors. As a result, GHG emissions in agriculture and Land Use, Land-Use Change and Forestry (LULUCF) in the three countries were 149 MtCO2eq/year and 1.0 GtCO2eq/year in 2005 and will increase 1.7 and 1.8 times up to 2030 in the BaU case. Indonesia is the largest emission country among them. We also found that no-regret mitigation technologies are expected to reduce 33MtCO2eq/year in 2030, which corresponds to 22% of agricultural emissions at the 2005 level. Under 10USD/tCO2eq of mitigation cost, 56MtCO2eq/year of emissions can be reduced by midseason drainage (MM) in rice cultivation, high efficient fertilizer application (HEF) to managed soils and Replacement of roughage with concentrates (RRC) etc. [ABSTRACT FROM AUTHOR]

Abstract: This paper presents the possibility for Thailand to become a low-carbon society (LCS). The methodology involves development of current CO2emission inventory, and quantification of socio-economic activity level in 2030. In this study, the increase of CO2 emissions is estimated based on i) 2030 BAU (business-as-usual) without mitigation measures, and ii) 2030 CM (climate change mitigation measures) assumptions of employed demand-side technologies as well as the potential to reduce the CO2 emissions by low-carbon measures available during 2005–2030. In this study, only selected climate change mitigation options, which have been found to be cost effective, are included in the 2030 CM scenario. Several comprehensive demand-side measures such as diffusion of low-carbon technologies in the residential sector, energy efficient buildings, energy efficient industry and fuel switching, and fuel substitution in the transport sector are proposed. Results show that i) the annual CO2 emissions in the base year of 2005 are 185,983kilo-ton (kt) of CO2, ii) under the scenario without climate change mitigation measures (the BAU scenario), year 2030 CO2 emissions would increase to 563,730kt-CO2 or 3.03 times that of the base year 2005, and iii) by adopting the selected climate change mitigation measures, CO2 emissions can be decreased approximately 28.4% compared to the 2030 BAU scenario, i.e. to 403,642kt-CO2. The research findings hope to contribute to sustainable energy and environmental transition of Thailand, one of the fastest growing economies in Southeast Asia, towards a Thai low carbon society. [Copyright &y& Elsevier]

Abstract: In order to realize a low-carbon society (LCS), it is necessary to formulate a comprehensive policy consisting of a large number of “options” (i.e., policies as well as technical and behavioral measures). Based on the concept of backcasting, this paper proposes a methodology and a model, called the backcasting model (BCM), that organizes a system of various LCS options and projects their detailed schedule toward a given target year. The methodology and model mainly focus on describing a complex system of LCS options and the consistency of their schedule. Other aspects such as the costs of LCS measures, stock dynamics of technologies, and effects of economic instruments are not explicitly considered. To permit quantitative treatment of various types of options, they are classified into several categories. The BCM calculates the schedule of the options under given quantitative information on the options and relationships between them. The methodology and model were applied to Kyoto City as an example. First, a quantitative snapshot of socioeconomic status and greenhouse gas (GHG) emissions was described. In the snapshot, a 45% reduction of GHG emissions compared with 1990 was achieved with moderate economic growth. The BCM was applied to about 130 options shown in an action plan of the Kyoto Municipal Government, and a schedule of the options was calculated. This methodology treats wide-ranging and complex low-carbon options in a quantitative and consistent manner and supports the policymaking process toward the realization of a low-carbon society. [Copyright &y& Elsevier]

Although several central and local governments around the world have set long term low-carbon targets, they do not always have concrete plans toward the goals. In order to reduce greenhouse gas (GHG) emission significantly, various kinds of measures in various sectors will be required. Some measures reduce GHG emissions directly and are called “direct measures” in this study. To implement those direct measures by the target year, indirect measures are also required, such as economic incentives, regulations, and urban planning. This study proposes a method to develop a concrete long-term schedule of direct and indirect measures, a “roadmap,” based on the idea of backcasting. To formulate the implementation of and relations between measures, and to estimate the concrete schedule to achieve the targets, we developed a model called “backcasting tool” (BCT). Given the information of measures including GHG emission reduction by measures, required resource input and maximum total resource input, and so on, BCT estimates the progress of the measures from the current to the target year. The method was applied in Kyoto City with a low-carbon target, 40% reduction in CO2 emission from fossil fuel by 2030 compared with 1990. Using BCT, we showed that a detailed schedule consists of about 100 measures classified into six fields. The result shows it is possible to achieve the target if all the measures, both direct and indirect, are implemented in time. [ABSTRACT FROM AUTHOR]

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Non-CO2 gas (CH4, N2O and F gas) emissions account for 25 percent of all greenhouse gas in the year of 2000. Main sources of CH4 and N2O emissions are agriculture-related activities such as enteric fermentation, paddy rice cultivation, soil management. A recursive dynamic CGE (Computer General Equilibrium) model has been developed to analyze greenhouse gas reduction options including non-CO2 gas abatement technologies. Multi-regional, multi-sectoral and multi-gas CGE model and simple climate change model simulated long-term climate stabilization emission path. Preliminary results showed that multi gas mitigation options including CH4 and N2O abatement technologies will reduce GDP loss more than CO2 only mitigation options for long-term climate stabilization, even though CO2 mitigation options will reduce not only CO2 emissions but non-CO2 gas emissions simultaneously. It is necessary to collect regional non-CO2 gas data (emission, technology options, and so on) and conduct more sensitivity analysis with computer simulation model to reduce uncertainty of non-CO2 gas. [ABSTRACT FROM AUTHOR]

The objectives of this study were to carry out a review of mitigation scenarios that have emerged since the Intergovernmental Panel on Climate Change (IPCC) Third Assessment Report (TAR), to update the current Emissions Scenarios Database with these scenarios, and to analyze emissions and mitigation scenarios. This article first discusses the characterization of mitigation scenarios and systematically classifies mitigation scenarios. Second, quantitative analyses on gross domestic product (GDP), population, carbon intensity, energy intensity, and carbon taxes are conducted at the regional level in the four regional aggregations used by the IPCC Special Report on Emissions Scenarios. Results show that the range of emissions trajectories is extensive and that the maximum potential mitigation of global CO2 emissions from the baseline level by 2100 is around 95%. There is a correlation between GDP growth and energy intensity improvement. The relationship between energy intensity improvement and carbon intensity reduction changes over the 21st century, with energy intensity improvement outweighing carbon intensity reduction in the first half of the century and carbon intensity reduction becoming more dominant in the latter half. Predicted carbon tax levels for 2100 range from around 50 to 1400 US$/t-C, although a uniform level of carbon tax brings about widely varying CO2 mitigation outcomes across different regions. The range of GDP loss, resulting from CO2 emissions mitigation, varies from -10% to 40% in 2100, with GDP losses in developing regions more evident than those in developed regions. [ABSTRACT FROM AUTHOR]

Evaluates investment as a robust adaptation strategy in response to projected climate change in China. Modern optimal economic growth theory; Relations between flood prevention infrastructure and flood damage to agricultural and non-agricultural sectors; Marginal adaptation costs to flood damage.

In order to respond to climate change, it is essential to describe possible future greenhouse gas (GHG) emission trajectories in both nonintervention and intervention terms. This paper analyzes long-term GHG mitigation emission scenarios according to alternative development paths in the world and major regions, based on the nonintervention emission scenarios quantified by the Asian-Pacific Integrated Model (AIM). AIM is revised and applied to the quantification of narrative storylines for scenarios of socioeconomic development, and GHG emissions from energy use, land-use change, and industrial production processes are simulated. A wide range of mitigation policies are adopted in this simulation as responses to the climate change. Several target stabilized levels–650, 550 and 450 ppmv–are analyzed. The results show that to achieve stabilization at a different GHG concentration level, a policy package is essential to reach the target concentration level, rather than a single policy. Energy efficiency improvement will be a key contributor to the reduction of GHG emissions as a result of the policy package. The mitigation cost could be at a medium level, without a large loss of economic growth. The developing world could significantly reduce GHG emissions compared with nonmitigation scenarios with sufficient knowledge transfer from developed countries. [ABSTRACT FROM AUTHOR]

We propose a new climate change mitigation assessment method focusing on agriculture, forestry, and land-use change sectors by coupling the computable general equilibrium (CGE) model with a bottom-up type technology model. The CGE model covers the entire economic market, but includes a rough description of mitigation measures, whereas the bottom-up type technology model takes into account abatement cost and mitigation effects of individual mitigation measures, but only focuses on a few sectors. The coupled framework enables us to connect relevant conditions and to complement the shortcomings of each model. As a test, we applied our method to Indonesia, which has set a national greenhouse gas emissions reduction target for 2020. A large proportion of Indonesia's greenhouse gas emissions are from the land-use sector. We assessed the differences in modeling behaviors between the CGE models with and without coupling the bottom-up type model. The two primary findings were: 1) consumption loss estimated by the coupled CGE (1.2%) was larger than the loss estimated by the uncoupled model (0.5%), because the emission reduction estimated by the bottom-up model was less than the standalone CGE's estimate; and 2) consumption loss caused by achieving the reduction target by 2020 in Indonesia strongly depends on the assumption of mitigation costs and available land area for the emission reduction measures. [ABSTRACT FROM AUTHOR]

We assessed the impact of climate change on rice production in Asia in comprehensive consideration of the process/parameter uncertainty in general circulation models (GCMs). After inputting future climate scenarios based on the projections of GCMs for three Special Report on Emissions Scenarios (SRES) (18 GCMs for A1B, 14 GCMs for A2, and 17 GCMs for B1) into a crop model, we calculated the average change in production (A CP), the standard deviation of the change in production (SD CP), and the probability of a production decrease (P PD) for each SRES scenario, taking into account the effect of CO2 fertilization. In the 2020s, P PD values were high for all SRES scenarios because the negative impacts of climate change were larger than the positive effects of CO2 fertilization in almost all climate scenarios in the near future. This suggests that it will be necessary to take immediate adaptive actions, regardless of the emission scenario, in the near future. In the 2080s, there were large differences in A CP, SD CP, and P PD among the SRES scenarios. The scenario with the highest atmospheric CO2 concentration, A2, showed a notable decrease in production and a high P PD in the 2080s compared with the other scenarios, despite having the largest CO2 fertilization effect. In addition, A2 had the largest SD CP among the SRES scenarios. On the other hand, the scenario with the lowest atmospheric CO2 concentration, B1, showed a small decrease in production, and a much smaller SD CP and a much lower P PD, than in the case of A2. These results for the 2080s suggest that a reduction in CO2 emissions in the long term has great potential not only to mitigate decreases in rice production, but also to reduce the uncertainty in these changes. [Copyright &y& Elsevier]