Woo, J.-H., Kim, Y. ORCID: https://orcid.org/0000-0002-5053-5068, Choi, K.-C., Lee, Y.-M., Jang, Y., Kim, J., Klimont, Z. ORCID: https://orcid.org/0000-0003-2630-198X, Kim, D.-G., Lee, J.-B., Jin, H., Hu, H., & Ahn, Y.-H. (2024). Development of a greenhouse gas - air pollution interactions and synergies model for Korea (GAINS-Korea). Scientific Reports 14 (1) e3372. 10.1038/s41598-024-53632-w.
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Abstract
This study aimed to create Greenhouse Gas - Air Pollution Interactions and Synergies (GAINS)-Korea, an integrated model for evaluating climate and air quality policies in Korea, modeled after the international GAINS model. GAINS-Korea incorporates specific Korean data and enhances granularity for enabling local government-level analysis. The model includes source-receptor matrices used to simulate pollutant dispersion in Korea, generated through CAMx air quality modeling. GAINS-Korea's performance was evaluated by examining different scenarios for South Korea. The business as usual scenario projected emissions from 2010 to 2030, while the air quality scenario included policies to reduce air pollutants in line with air quality and greenhouse gas control plans. The maximum feasible reduction scenario incorporated more aggressive reduction technologies along with air quality measures. The developed model enabled the assessment of emission reduction effects by both greenhouse gas and air pollutant emission reduction policies across 17 local governments in Korea, including changes in PM2.5 (particulate matter less than 2.5 μm) concentration and associated benefits, such as reduced premature deaths. The model also provides a range of visualization tools for comparative analysis among different scenarios, making it a valuable resource for policy planning and evaluation, and supporting decision-making processes.
Item Type: | Article |
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Research Programs: | Energy, Climate, and Environment (ECE) Energy, Climate, and Environment (ECE) > Pollution Management (PM) |
Depositing User: | Luke Kirwan |
Date Deposited: | 12 Feb 2024 08:19 |
Last Modified: | 12 Feb 2024 08:19 |
URI: | https://pure.iiasa.ac.at/19492 |
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