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.

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.

The shift in consumer preferences for large-sized cars has increased the energy intensity (EI) of passenger cars, while growth in battery electric vehicle (BEV) sales has decreased EI in recent years in South Korea. In order to lower passenger cars’ EI, the South Korean government has implemented the Corporate Average Fuel Economy (CAFE) standards with a credit system, in which the sale of one energy-efficient car (for example, a BEV) can get multiple credits. This study analyzes CAFE standards in terms of both the EI improvement sensitivity scenarios and the degree of credits for BEVs and fuel cell electric vehicles (FCEVs) by using the Global Change Assessment Model (GCAM). In this study, passenger cars include small, medium, and large sedans, sport utility vehicles (SUVs) of internal combustion engine vehicles (ICEVs), BEVs, and FCEVs. The findings of this study are as follows: First, from the policy design perspective, a proper setting of the credit system for BEVs and FCEVs is a very important variable for automakers to achieve CAFE standards. Second, from the technology promotion perspective, active promotion of fuel efficiency improvements through CAFE standards are important since Better-EI and Best-EI scenarios are found to achieve CAFE standards even when a BEV or a FCEV receives a credit of one car sale in 2030.

In this study, we discuss the modeling of domestic transport sector using GCAM(Global Change Assessment Model). The GCAM is one of integrated assessment models widely used in internationally modeling community, and applied for the evaluation of IPCC 5th Report. Nevertheless, it is noted that there are a considerable number of problems in its application to domestic transport sector. First, the base year information of GCAM for detailed transportation service demand is found not consistent with national statistics. Second, the transportation sector simulation results do not properly reflect the past trends of service demand. Thus, the base year service demand is carefully matched with the detailed national statistics. In addition, the existing models were checked and modified so that the simulation results of service demand can accurately reflect past trends of national statistics. As a result, it is reported in detail how the current GCAM simulation results are corrected and how the trend of past transportation sector service demands is properly reflected. This study is expected to be useful as a basic tool for future scenario analysis for transportation policy, technology evaluation and greenhouse gas reduction measures.

No abstract