*1.2. Main Objectives of This Study*

Studies have widely used an integrated assessment model (IAM) for analyzing environmental policy within inter-related systems such as the economy, energy, land-use, agriculture, and climate [13]. IAM has also been used for emission projections, mortality costs, and air quality management for PM2.5 (Table 1).

CPFDM was established based on the following studies but the studies have some shortcomings. Kim et al. [14] prioritized PM reduction policies using the Analytic Hierarchy Process (AHP) and suggested 'Mandatory reduction of air pollution in the manufacturing industry and the suspension of such factories operation' as the top priority. Since they did not consider provincial emissions patterns, their suggestion may not be applicable to some provinces. For example, policies associated with diesel vehicle reduction might have been given a higher priority than the suggested policy in the Seoul metropolitan area if Kim et al. [14] had taken into account provincial emission patterns. In this sense, our study can make up the gap in Kim et al.'s study.

For the computation of PM2.5, NOx, and SOx concentrations at monthly and grid levels, the Community Multiscale Air Quality (CMAQ) model was used with the national emissions inventory [15–17]. Anthropogenic emissions control is constrained in socioeconomics assumptions such as population and economic growth, as well as technology development assumptions [18]. However, since some studies are based on the point of view of atmospheric chemical reactivity, they do not consider socioeconomics assumptions. Besides, there is also a study which estimates social costs of PM2.5 [19].


**Table 1.** Previous studies on anthropogenic PM2.5 emissions using IAM.

<sup>1</sup> Global Change Assessment Model-USA developed by PNNL/JGCRI; <sup>2</sup> Regional Air Pollution INformation and Simulation developed by IIASA; <sup>3</sup> Environmental Protection Agency-MARKet Allocation developed by EPA; <sup>4</sup> and Greenhouse gas Air pollution Interactions and Synergies developed by IIASA.

An analysis of cross-sectoral dynamics is a pre-requisite for preventing unexpected harm of the spillover effects in multiple sectors, but there are few studies on how the policy impact of PM2.5 emissions changes in multiple sectors. Hence, using IAM can remedy the shortcomings of previous studies. However, to the best of our knowledge IAM has not been applied for tackling PM2.5 issues in Korea. Moreover, IAM is also capable of analyzing PM2.5 at the provincial level and this too has not been developed yet by researchers.

Hence, the first goal of this study is modeling air pollutant emissions using IAM that represents Korean province partial resolution (GCAM-Korea). This study focuses on the road transportation sector in GCAM-Korea as the first step. Pollutant coverage is primary PM2.5 as well as the precursors NOx, SOx, VOC, and NH3. The second goal is assessing the ZEV subsidy policy's impact on air pollutant emissions across the road transportation sector and provinces.
