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With its target of becoming a middle-income country by 2025, Ethiopia has set ambitious targets in its Growth Transformation Plan (GTP) II, such as increasing power generation capacity from 4.18 to 17.21 GW during the 2016-2020 period. However, according to the 2015 IEA energy balance table, Ethiopia depends heavily on biomass for its final energy use. In final energy service sectors, biomass takes more than 90% of the final energy consumption (36.9 out of 40.9 MTOE), 99% of which is consumed in the residential sector. Therefore, it is very important to achieve biomass utilization in the energy sector targets of Ethiopia. This paper aims to analyze the biomass consumption in the Ethiopia energy system, and discuss related policies. An integrated assessment model is chosen for its national energy modeling, and to simulate policy scenarios in a comprehensive and consistent manner. After building a reference case, three scenarios are developed: (1) higher Gross Domestic Product (GDP) and urbanization rate, (2) efficiency improvement of biomass technologies, and (3) sensitivity analysis of urbanization. It is found that biomass still holds the largest share of energy consumption in the future, which increases even more in the high GDP and urbanization scenario. Increasing efficiency of biomass technology can reduce biomass consumption, but the "rebound effect" is observed, which increases the energy service demand, thus dampening the effect of biomass efficiency improvement.

South Korea has been suffering from high PM2.5 pollution. Previous studies have contributed to establishing PM2.5 mitigation policies but have not considered provincial features and sector-interactions. In that sense, the integrated assessment model (IAM) could complement the shortcomings of previous studies. IAM, capable of analyzing PM2.5 pollution levels at the provincial level in Korea, however, has not been developed yet. Hence, this study (i) expands on IAM which can represent provincial-level spatial resolution in Korea (GCAM-Korea) with air pollutant emissions modeling which focuses on the road transportation sector and (ii) examines the zero-emission vehicles (ZEVs) subsidy policy’s effects on PM2.5 mitigation using the expanded GCAM-Korea. Simulation results show that PM2.5 emissions decrease by 0.6–4.1% compared to the baseline, and the Seoul metropolitan area contributes 38–44% to the overall PM2.5 emission reductions. As the ZEVs subsidy is weighted towards the light-duty vehicle 4-wheels (LDV4W) sector, various spillover effects are found: ZEVs’ share rises intensively in the LDV4W sector leading to an increase in its service costs, and at the same time, driving bus service costs to become relatively cheaper. This, in turn, drives an increase in bus service demand and emissions discharge. Furthermore, this type of impact of the ZEVs subsidy policy does not reduce internal combustion engine vehicles (ICEVs) in freight trucks, although diesel freight trucks are a major contributor to PM2.5 emissions and also to NOx.

No abstract

Integrated assessment modeling at a higher spatial scale is a prerequisite for deriving region-specific implications from the model. The Global Change Assessment Model (GCAM) was chosen for GCAM-Korea, a detailed integrated assessment model (IAM) of Korea’s socioeconomic and energy systems. GCAM-Korea is developed based on GCAM-USA. Data for 16 provinces have been collected from various sources. Some data have been pre-processed to fit within the specific structure of GCAM-USA data. Other types of data were newly added through new structures. The model results were validated to be compatible with historical trends. It was found that provincial energy plans or policies could be compiled in detail using the proposed model while maintaining consistency with national level modeling results. The cross-border air pollution issue in Northeast Asia could also be addressed by combining GCAM-Korea and air quality models in the future.