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.
Highlights
In the development of an integrated assessment model (IAM), higher spatial resolution offers various advantages
Rotmans [2] highlighted two advantages of regional IAM: i) Integrated assessments can focus on concrete societal problem, issues which are already at stake in a specific region, ii) Integrated assessments can be made geographically-explicit, which allows for visualizing the trade-offs between problems, sectors, resources and scale levels to be made
End-Use Sectors: 1 Industry; 2 Transportation; 3 Household; 4 Service; 5 Residential; 6 Commercial; 7 Agriculture; 8 Public; 9 Transformation sectors include power generation, hydrogen generation and oil refining sector; 10 Sejong (SJ)’s energy plan is established with two models, Research Institute for Energy, Environment and Economy (RIEEE). With these points in mind, this study aims to (i) develop a Korean provincial-level energy system model, Global Change Assessment Model (GCAM)-Korea, so that provincial heterogeneity can be captured, (ii) open the model for reproducibility and transparency (See Appendix A) and (iii) compare the model results with historical values for empirical validation
Summary
In the development of an integrated assessment model (IAM), higher spatial resolution offers various advantages. Rotmans [2] highlighted two advantages of regional IAM: i) Integrated assessments can focus on concrete societal problem, issues which are already at stake in a specific region, ii) Integrated assessments can be made geographically-explicit, which allows for visualizing the trade-offs between problems, sectors, resources and scale levels to be made. According to the previous studies, capturing the heterogeneity within regions (nations, states, provinces, even GIS (Geographic information system)-level) is a main motivation for modeling IAM at a more detailed spatial scale. This begs the question of just how detailed a model’s spatial resolution should be. In the case of GCAM-Korea, the rationale for developing provincial-level modeling is discussed below
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