Air quality co-benefits from climate mitigation for human health in South Korea

• 藤森, 真一郎

• Xie, Yang

• Dai, Hancheng

• Fujimori, Shinichiro

• Hijioka, Yasuaki

• Honda, Yasushi

• Hashizume, Masahiro

• Masui, Toshihiko

• Hasegawa, Tomoko

• Xu, Xinghan

• Yi, Kan

• Kim, Ho

抄録

Climate change mitigation efforts to reduce greenhouse gas (GHG) emissions have associated costs, but there are also potential benefits from improved air quality, such as public health improvements and the associated cost savings. A multidisciplinary modeling approach can better assess the co-benefits from climate mitigation for human health and provide a justifiable basis for establishment of adequate climate change mitigation policies and public health actions. An integrated research framework was adopted by combining a computable general equilibrium model, an air quality model, and a health impact assessment model, to explore the long-term economic impacts of climate change mitigation in South Korea through 2050. Mitigation costs were further compared with health-related economic benefits under different socioeconomic and climate change mitigation scenarios. Achieving ambitious targets (i.e., stabilization of the radiative forcing level at 3.4W/m2) would cost 1.3-8.5 billion USD in 2050, depending on varying carbon prices from different integrated assessment models. By contrast, achieving these same targets would reduce costs by 23 billion USD from the valuation of avoided premature mortality, 0.14 billion USD from health expenditures, and 0.38 billion USD from reduced lost work hours, demonstrating that health benefits alone noticeably offset the costs of cutting GHG emissions in South Korea.

収録刊行物

• Environment international

  Environment international 136 2020-03

  Elsevier BV

キーワード

• Climate mitigation
• Air pollution
• Health impact assessment
• Co-benefit analysis
• CGEIMED Model

詳細情報

• CRID: 1051130853409451392
• NII論文ID: 120006895432
• ISSN: 01604120
• HANDLE: 2433/255849
• 本文言語コード: en
• 資料種別: journal article
• データソース種別:
  • IRDB
  • CiNii Articles