Global S&T Development Trend Analysis Platform of Resources and Environment
DOI | 10.5194/acp-19-1097-2019 |
Estimation of ground-level particulate matter concentrations through the synergistic use of satellite observations and process-based models over South Korea | |
Park, Seohui1; Shin, Minso1; Im, Jungho1; Song, Chang-Keun1; Choi, Myungje2,3; Kim, Jhoon2; Lee, Seungun4; Park, Rokjin4; Kim, Jiyoung5; Lee, Dong-Won6; Kim, Sang-Kyun6 | |
2019-01-28 | |
发表期刊 | ATMOSPHERIC CHEMISTRY AND PHYSICS |
ISSN | 1680-7316 |
EISSN | 1680-7324 |
出版年 | 2019 |
卷号 | 19期号:2页码:1097-1113 |
文章类型 | Article |
语种 | 英语 |
国家 | South Korea; USA |
英文摘要 | Long-term exposure to particulate matter (PM) with aerodynamic diameters < 10 (PM10) and 2.5 mu m (PM2.5) has negative effects on human health. Although station-based PM monitoring has been conducted around the world, it is still challenging to provide spatially continuous PM information for vast areas at high spatial resolution. Satellite-derived aerosol information such as aerosol optical depth (AOD) has been frequently used to investigate ground-level PM concentrations. In this study, we combined multiple satellite-derived products including AOD with model-based meteorological parameters (i. e., dew-point temperature, wind speed, surface pressure, planetary boundary layer height, and relative humidity) and emission parameters (i. e., NO, NH3, SO2, primary organic aerosol (POA), and HCHO) to estimate surface PM concentrations over South Korea. Random forest (RF) machine learning was used to estimate both PM10 and PM2.5 concentrations with a total of 32 parameters for 2015-2016. The results show that the RF-based models produced good performance resulting in R-2 values of 0.78 and 0.73 and root mean square errors (RMSEs) of 17.08 and 8.25 mu gm(-3) for PM10 and PM2.5, respectively. In particular, the proposed models successfully estimated high PM concentrations. AOD was identified as the most significant for esti-mating ground-level PM concentrations, followed by wind speed, solar radiation, and dew-point temperature. The use of aerosol information derived from a geostationary satellite sensor (i. e., Geostationary Ocean Color Imager, GOCI) resulted in slightly higher accuracy for estimating PM concentrations than that from a polar-orbiting sensor system (i. e., the Moderate Resolution Imaging Spectroradiometer, MODIS). The proposed RF models yielded better performance than the process-based approaches, particularly in improving on the underestimation of the process-based models (i. e., GEOS-Chem and the Community Multiscale Air Quality Modeling System, CMAQ). |
领域 | 地球科学 |
收录类别 | SCI-E |
WOS记录号 | WOS:000456990800003 |
WOS关键词 | AEROSOL OPTICAL DEPTH ; PM2.5 CONCENTRATIONS ; PM10 CONCENTRATION ; SOLAR-RADIATION ; AIR-POLLUTION ; KM RESOLUTION ; RANDOM FOREST ; LAND-USE ; CHINA ; PRODUCTS |
WOS类目 | Environmental Sciences ; Meteorology & Atmospheric Sciences |
WOS研究方向 | Environmental Sciences & Ecology ; Meteorology & Atmospheric Sciences |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://119.78.100.173/C666/handle/2XK7JSWQ/17239 |
专题 | 地球科学 |
作者单位 | 1.Ulsan Natl Inst Sci & Technol, Sch Urban & Environm Engn, Ulsan 44919, South Korea; 2.Yonsei Univ, Dept Atmospher Sci, Seoul 03722, South Korea; 3.CALTECH, Jet Prop Lab, Pasadena, CA USA; 4.Seoul Natl Univ, Sch Earth & Environm Sci, Seoul 08826, South Korea; 5.Natl Inst Environm Res, Global Environm Res Div, Climate & Air Qual Res Dept, Incheon 22689, South Korea; 6.Natl Inst Environm Res, Environm Satellite Ctr, Climate & Air Qual Res Dept, Incheon 22689, South Korea |
推荐引用方式 GB/T 7714 | Park, Seohui,Shin, Minso,Im, Jungho,et al. Estimation of ground-level particulate matter concentrations through the synergistic use of satellite observations and process-based models over South Korea[J]. ATMOSPHERIC CHEMISTRY AND PHYSICS,2019,19(2):1097-1113. |
APA | Park, Seohui.,Shin, Minso.,Im, Jungho.,Song, Chang-Keun.,Choi, Myungje.,...&Kim, Sang-Kyun.(2019).Estimation of ground-level particulate matter concentrations through the synergistic use of satellite observations and process-based models over South Korea.ATMOSPHERIC CHEMISTRY AND PHYSICS,19(2),1097-1113. |
MLA | Park, Seohui,et al."Estimation of ground-level particulate matter concentrations through the synergistic use of satellite observations and process-based models over South Korea".ATMOSPHERIC CHEMISTRY AND PHYSICS 19.2(2019):1097-1113. |
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