연세대학교 · 환경과학
Sujung Go 교수의 연구실은 대기 중 에어로졸, 특히 흡수성 물질인 철산화물(헤마티트 및 고에티트)과 연기 황산염, 블랙카본, 브라운카본 등 흡수성 에어로졸의 광학적 특성과 기후 영향을 중심으로 연구를 진행합니다. 우주기반 센서(DSCOVR/EPIC, GOSAT, OMI 등)를 활용한 고해상도 자외선-가시광선 스펙트럼 데이터를 기반으로 에어로졸의 농도, 분포, 철산화물 비율 및 고도 분포를 정량적으로 추정하는 데 전문성을 가집니다. 특히 단일 채널 UV 데이터를 활용한 신규 UVAI 추정 기법과 MAIAC 알고리즘을 통한 장기적 수직 분포 분석은 기후 모델링과 대기 오염 평가에 기여하고 있습니다.
표시된 성과는 수집된 데이터 기준으로 산출되며, 일부 차이가 있을 수 있습니다.
The retrieval of optimal aerosol datasets by the synergistic use of hyperspectral ultraviolet (UV)–visible and broadband meteorological imager (MI) techniques was investigated. The Aura Ozone Monitoring Instrument (OMI) Level 1B (L1B) was used as a proxy for hyperspectral UV–visible instrument data to which the Geostationary Environment Monitoring Spectrometer (GEMS) aerosol algorithm was applied. Moderate-Resolution Imaging Spectroradiometer (MODIS) L1B and dark target aerosol Level 2 (L2) data
The Ultra-Violet Aerosol Index (UVAI) is a practical parameter for detecting aerosols that absorb UV radiation, especially where other aerosol retrievals fail, such as over bright surfaces (e.g., deserts and clouds). However, typical UVAI retrieval requires at least two UV channels, while several satellite instruments, such as the Thermal And Near infrared Sensor for carbon Observation Cloud and Aerosol Imager (TANSO-CAI) instrument onboard a Greenhouse gases Observing SATellite (GOSAT), provide
Abstract. The iron-oxide content of dust in the atmosphere and most notably its apportionment between hematite (α-Fe2O3) and goethite (α-FeOOH) are key determinants in quantifying dust's light absorption, its top of atmosphere UV radiances used for dust monitoring, and ultimately shortwave dust direct radiative effects (DRE). Hematite and goethite column mass concentrations and iron-oxide mass fractions of total dust mass concentration were retrieved from the Deep Space Climate Observatory (DSCO
<strong class="journal-contentHeaderColor">Abstract.</strong> The iron-oxide content of dust in the atmosphere and most notably its apportionment between hematite (<span class="inline-formula"><i>α</i></span>-Fe<span class="inline-formula"><sub>2</sub></span>O<span class="inline-formula"><sub>3</sub></span>) and goethite (<span class="inline-formula"><i>α</i></span>-FeOOH) are key determinants in quantifying dust's light absorption, its top of atmosphere ultraviolet (UV) radiances used for dus
<strong class="journal-contentHeaderColor">Abstract.</strong> The iron-oxide content of dust in the atmosphere and most notably its apportionment between hematite (<span class="inline-formula"><i>α</i></span>-Fe<span class="inline-formula"><sub>2</sub></span>O<span class="inline-formula"><sub>3</sub></span>) and goethite (<span class="inline-formula"><i>α</i></span>-FeOOH) are key determinants in quantifying dust's light absorption, its top of atmosphere ultraviolet (UV) radiances used for dus
<strong class="journal-contentHeaderColor">Abstract.</strong> The iron-oxide content of dust in the atmosphere and most notably its apportionment between hematite (<span class="inline-formula"><i>α</i></span>-Fe<span class="inline-formula"><sub>2</sub></span>O<span class="inline-formula"><sub>3</sub></span>) and goethite (<span class="inline-formula"><i>α</i></span>-FeOOH) are key determinants in quantifying dust's light absorption, its top of atmosphere ultraviolet (UV) radiances used for dus
This study investigates the vertical distribution and seasonal climatology of absorbing iron-oxide minerals, specifically hematite and goethite, in atmospheric dust using the updated MAIAC EPIC version 3 algorithm. Leveraging data from July 2015 to December 2023, the key innovation is the improved Level 2 product which now incorporates Aerosol Layer Height (ALH), enabling the first-ever long-term characterization of their vertical and seasonal distribution globally. Our analysis reveals distinct
Aerosol optical depth (AOD) data fusion for aerosol datasets obtained from the Geostationary Korea Multi-Purpose Satellite (GEO-KOMPSAT; GK) series was conducted through the application of both statistical and deep neural network (DNN)-based methodologies. The GK mission incorporates the Advanced Meteorological Imager (AMI) on GK-2A, as well as the Geostationary Environment Monitoring Spectrometer (GEMS) and Geostationary Ocean Color Imager-II (GOCI-II) on GK-2B. The statistical fusion approach
<strong class="journal-contentHeaderColor">Abstract.</strong> Wildfires and agricultural burning generate seemingly increasing smoke aerosol emissions, impacting societal and natural ecosystems. To understand smoke’s effects on climate and public health, we analyzed the spatiotemporal distribution of smoke aerosols, focusing on two major light-absorbing components, black carbon (BC) and brown carbon (BrC) aerosols. Using NASA’s Earth Polychromatic Imaging Camera (EPIC) instrument abo
The iron-oxide content of dust in the atmosphere and most notably its apportionment between hematite (α-Fe2O3) and goethite (α-FeOOH) are key determinants in quantifying dust's light absorption, its top of atmosphere UV radiances used for dust monitoring, and ultimately shortwave dust direct radiative effects (DRE). Hematite and goethite column mass concentrations and iron-oxide mass fractions of total dust mass concentration were retrieved from the Deep Space Climate Observatory (DSCOVR) Earth
