Faculty Research Profile
Yujin Oak
학력
・ 2023: Ph.D., Earth and Environmental Sciences, Seoul National University
・ 2016: B.S., Earth and Environmental Sciences, Korea University
주요 경력
・ 2025~present: Assistant Professor, UNIST
・ 2023~2025: Postdoctoral Fellow, Harvard University
수상/학회/외부활동
・ 2023: Outstanding Ph.D. Dissertation Award (Korean Meteorological Society)
・ 2023: Young Professionals (NET) Sponsorship (Korean Federation of Science and Technology Societies)
・ 2021: Student Colloquium Excellent Presentation Award (Korean Society for Atmospheric Environment)
대기화학 모델링 연구실
Atmospheric Chemistry and Emissions Modeling Group
대기화학 모델링(ACHEM) 연구실은 인간이 생활하면서 가장 오랜 시간동안 접하며 들이마시고 내쉬는 대기 속에 포함된 가스상과 입자상 오염 물질들을 연구합니다. 대기오염과 기후변화 유발 물질들의 배출원과 화학적 생성 및 소멸 과정에 대한 이해를 높여 모의 정확도를 향상 시키고, 생태계 및 기후에 미치는 사회경제적인 영향을 평가하기 위해 3차원 대기화학 수송 모델 및 머신러닝 기법과 더불어 인공위성, 항공, 지상 관측과 같은 다양한 지구 관측 자료를 활용합니다.
The Atmospheric Chemistry and Emissions Modeling (ACHEM) group studies gaseous and particulate pollutants contained in the air we breathe. We utilize 3-D chemical transport models, machine learning approaches, and various Earth observations including satellites, aircraft, and ground monitoring networks to identify sources, better predict, and understand the chemical fate of air pollutants and greenhouse gases.
The Atmospheric Chemistry and Emissions Modeling (ACHEM) group studies gaseous and particulate pollutants contained in the air we breathe. We utilize 3-D chemical transport models, machine learning approaches, and various Earth observations including satellites, aircraft, and ground monitoring networks to identify sources, better predict, and understand the chemical fate of air pollutants and greenhouse gases.
연구분야
대기화학, 기후변화, 대기질 모의, 탄소 배출량 산정 / Atmospheric chemistry, Climate change, Air quality modeling, Carbon emissions
Atmospheric chemistry, Climate change, Air quality modeling, Carbon emissions
연구 희망분야
수치모델, 머신러닝, 위성관측, 지상관측을 활용한 통합 탄소 모니터링 / Integrated carbon monitoring using numerical models, machine learning, satellites, and ground-based measurements
Integrated carbon monitoring using numerical models, machine learning, satellites, and ground-based measurements
연구주제
・ 대기질 모의: 정지궤도 환경위성 군집을 활용한 대기질 모델 개선, 전구체 배출량 산정, 지상 대기질 자료 생산, 사회경제적 영향 평가
・ 온실가스 모니터링: 모델과 위성을 활용한 온실가스(메탄, CO₂) 배출량의 하향식 산정, 탄소중립을 위한 국가결정기여(NDC) 이행 현황 평가
・ Air quality (AQ) assessment: leverage geostationary satellite constellation for AQ to improve models, quantify precursor emissions, produce surface AQ data, and assess socioeconomic impacts
・ Greenhouse gas (GHG) monitoring: leverage area flux and point source imaging satellites to identify major sources and trends of GHGs (methane, CO₂), and assess progress of nationally determined contributions (NDCs) for carbon neutrality
・ Air quality (AQ) assessment: leverage geostationary satellite constellation for AQ to improve models, quantify precursor emissions, produce surface AQ data, and assess socioeconomic impacts
・ Greenhouse gas (GHG) monitoring: leverage area flux and point source imaging satellites to identify major sources and trends of GHGs (methane, CO₂), and assess progress of nationally determined contributions (NDCs) for carbon neutrality
국가연구개발사업 기술 분류체계
국가과학기술표준분류
ND. 지구과학(지구/대기/해양/천문) > ND04. 대기과학 > ND0404. 대기화학
논문
・ ATMOSPHERIC CHEMISTRY AND PHYSICS, Air quality trends and regimes in South Korea inferred from 2015−2023 surface and satellite observations, Oak, Y. J., Jacob, D.J., Pendergrass, D.C., et al. (2025)
・ ATMOSPHERIC MEASUREMENT TECHNIQUES, A bias-corrected GEMS geostationary satellite product for nitrogen dioxide using machine learning to enforce consistency with the TROPOMI satellite instrument. Oak, Y. J., Jacob, D.J., Balasus, N., et al. (2024)
・ SCIENCE OF THE TOTAL ENVIRONMENT, Future air quality and premature mortality in Korea. Oak, Y. J., Park, R.J., Lee, J.-T., Byun, G. (2023)