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Abstract This paper explores how China’s household consumption patterns over the period 2005–2050 influence the total energy demand and carbon dioxide (CO2) emissions in two baseline scenarios, and how it influences carbon prices as well as the economic cost in the corresponding carbon mitigation scenarios. To this end we first put forward two possible household consumption expenditure patterns up to 2050 using the Working–Leser model, taking into account total expenditure increase and urbanization. For comparison, both expenditure patterns are then incorporated in a hybrid recursive dynamic computable general equilibrium model. The results reveal that as income level increases in the coming decades, the direct and indirect household energy requirements and CO2 emissions would rise drastically. When household expenditure shifts from material products and transport to service-oriented goods, around 21,000 mtce 1 of primary energy and 45 billion tons of CO2 emissions would be saved over the 45-year period from 2005 to 2050. Moreover, carbon prices in the dematerialized mitigation scenario would fall by 13% in 2050, thus reducing the economic cost.

Abstract This paper explores how China’s household consumption patterns over the period 2005–2050 influence the total energy demand and carbon dioxide (CO2) emissions in two baseline scenarios, and how it influences carbon prices as well as the economic cost in the corresponding carbon mitigation scenarios. To this end we first put forward two possible household consumption expenditure patterns up to 2050 using the Working–Leser model, taking into account total expenditure increase and urbanization. For comparison, both expenditure patterns are then incorporated in a hybrid recursive dynamic computable general equilibrium model. The results reveal that as income level increases in the coming decades, the direct and indirect household energy requirements and CO2 emissions would rise drastically. When household expenditure shifts from material products and transport to service-oriented goods, around 21,000 mtce 1 of primary energy and 45 billion tons of CO2 emissions would be saved over the 45-year period from 2005 to 2050. Moreover, carbon prices in the dematerialized mitigation scenario would fall by 13% in 2050, thus reducing the economic cost.

Abstract This paper performs energy model hindcasting which compared the historical energy simulation results with the observations. We used one of the Integrated Assessment Models and simulated global historical energy consumption from 1981 to 2010 associated with exogenous socioeconomic assumptions, as is typically performed for future scenario. The simulation period was chosen with consideration of data availability and structural constancy of the model. Based on comparison with observations, there are three main findings. First, the global aggregated primary energy shows high reproducibility. In terms of energy source specific results, the fitness in electricity, coal, and biomass consumption were high. However, that of crude oil and natural gas is lower than others. This could be due to the price elasticity assumption, implying that the model can be improved with regard to this element. Second, the reproducibility increases as the simulation is close to the base year 2005. Third, although the global aggregated information shows high reproducibility, some disaggregated regions have lower reproducibility. Furthermore, high income countries tend to show higher reproducibility than in low income countries. Given the uncertainties in the ability of IAMs to reproduce certain aspects of the energy system, forecasts must be treated with caution.

Abstract This paper performs energy model hindcasting which compared the historical energy simulation results with the observations. We used one of the Integrated Assessment Models and simulated global historical energy consumption from 1981 to 2010 associated with exogenous socioeconomic assumptions, as is typically performed for future scenario. The simulation period was chosen with consideration of data availability and structural constancy of the model. Based on comparison with observations, there are three main findings. First, the global aggregated primary energy shows high reproducibility. In terms of energy source specific results, the fitness in electricity, coal, and biomass consumption were high. However, that of crude oil and natural gas is lower than others. This could be due to the price elasticity assumption, implying that the model can be improved with regard to this element. Second, the reproducibility increases as the simulation is close to the base year 2005. Third, although the global aggregated information shows high reproducibility, some disaggregated regions have lower reproducibility. Furthermore, high income countries tend to show higher reproducibility than in low income countries. Given the uncertainties in the ability of IAMs to reproduce certain aspects of the energy system, forecasts must be treated with caution.

Abstract Renewable energy has a critical role in limiting the greenhouse gas (GHG) emissions. This paper assesses the implication of aligning renewable energy deployment target with national emission reduction target for mitigation cost. The assessment methodology uses Asia-Pacific Integrated Assessment/computable general equilibrium (AIM/CGE) model to determine the mitigation cost in terms of GDP and welfare loss under alternative renewable targets in different climate-constrained scenarios. A range of country-specific emission constraints is taken to address the uncertainties related to global emission pathway and emission entitlement scheme. Comparative results show that China needs to increase its share of non-fossil fuel significantly in the primary energy mix to achieve the stringent emission reduction target compared to India. The mitigation cost in terms of economic and welfare loss can be reduced by increasing the penetration of the renewable energy to achieve the same emission reduction target. The modeling results show that coordinated national climate and renewable energy policies help to achieve the GHG emission reduction target in an efficient and cost-effective manner.

Abstract Renewable energy has a critical role in limiting the greenhouse gas (GHG) emissions. This paper assesses the implication of aligning renewable energy deployment target with national emission reduction target for mitigation cost. The assessment methodology uses Asia-Pacific Integrated Assessment/computable general equilibrium (AIM/CGE) model to determine the mitigation cost in terms of GDP and welfare loss under alternative renewable targets in different climate-constrained scenarios. A range of country-specific emission constraints is taken to address the uncertainties related to global emission pathway and emission entitlement scheme. Comparative results show that China needs to increase its share of non-fossil fuel significantly in the primary energy mix to achieve the stringent emission reduction target compared to India. The mitigation cost in terms of economic and welfare loss can be reduced by increasing the penetration of the renewable energy to achieve the same emission reduction target. The modeling results show that coordinated national climate and renewable energy policies help to achieve the GHG emission reduction target in an efficient and cost-effective manner.

Abstract A reduction of energy service demand is a climate mitigation option, but its effectiveness has never been quantified. We quantify the effectiveness of energy service demand reduction in the building, transport, and industry sectors using the Asia-Pacific Integrated Assessment/Computable General Equilibrium (AIM/CGE) model for the period 2015–2050 under various scenarios. There were two major findings. First, a 25% energy service demand reduction in the building, transport, and basic material industry sectors would reduce the GDP loss induced by climate mitigation from 4.0% to 3.0% and from 1.2% to 0.7% in 2050 under the 450 ppm and 550 ppm CO 2 equivalent concentration stabilization scenarios, respectively. Second, the effectiveness of a reduction in the building sector׳s energy service demand would be higher than those of the other sectors at the same rate of the energy service demand reduction. Furthermore, we also conducted a sensitivity analysis of different socioeconomic conditions, and the climate mitigation target was found to be a key determinant of the effectiveness of energy service demand reduction measures. Therefore, more certain climate mitigation targets would be useful for the decision makers who design energy service demand reduction measures.

Abstract A reduction of energy service demand is a climate mitigation option, but its effectiveness has never been quantified. We quantify the effectiveness of energy service demand reduction in the building, transport, and industry sectors using the Asia-Pacific Integrated Assessment/Computable General Equilibrium (AIM/CGE) model for the period 2015–2050 under various scenarios. There were two major findings. First, a 25% energy service demand reduction in the building, transport, and basic material industry sectors would reduce the GDP loss induced by climate mitigation from 4.0% to 3.0% and from 1.2% to 0.7% in 2050 under the 450 ppm and 550 ppm CO 2 equivalent concentration stabilization scenarios, respectively. Second, the effectiveness of a reduction in the building sector׳s energy service demand would be higher than those of the other sectors at the same rate of the energy service demand reduction. Furthermore, we also conducted a sensitivity analysis of different socioeconomic conditions, and the climate mitigation target was found to be a key determinant of the effectiveness of energy service demand reduction measures. Therefore, more certain climate mitigation targets would be useful for the decision makers who design energy service demand reduction measures.

Abstract The curtailment and storage associated with the fluctuation of electricity supplied by variable renewable energy (VRE) may limit its penetration into electricity systems. Therefore, these factors need to be explicitly treated in the integrated assessment models (IAMs). This study improves the representation of curtailment and storage of VRE in a computable general equilibrium (CGE) model. With the data generated from an hourly power sector model, curtailment and storage of VRE electricity are treated as a function of the shares of solar and wind in the electricity mix. This relationship is incorporated into a CGE model and we also updated the VRE costs and resource potential. The results show that with such improvement, by 2100, in a 450 ppm atmospheric CO 2 equivalent concentration (henceforth ppm) scenario, some electricity generated from VRE is either curtailed (2.1%) or needs to be stored (2.9%). In contrast, if VRE fluctuation is not considered, the long-term global economic cost of carbon mitigation is significantly underestimated (by 52%) in the same scenario. Conversely, updating the VRE costs and resource potential leads to a decrease in mitigation costs. Our simulation implies that the fluctuation of VRE cannot be ignored and needs to be incorporated into CGE models. Moreover, in addition to storage with batteries, many other options are available to reduce curtailment of VRE. The top-down type CGE model has limitations to fully incorporate all aspects due to its limited spatial, temporal, and technological resolution.