Global S&T Development Trend Analysis Platform of Resources and Environment
DOI | 10.1002/2017JD028009 |
First Top-Down Estimates of Anthropogenic NOx Emissions Using High-Resolution Airborne Remote Sensing Observations | |
Souri, Amir H.1; Choi, Yunsoo1; Pan, Shuai1; Curci, Gabriele2,3; Nowlan, Caroline R.4; Janz, Scott J.5; Kowalewski, Matthew G.5,6; Liu, Junjie7; Herman, Jay R.5,8; Weinheimer, Andrew J.9 | |
2018-03-27 | |
发表期刊 | JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES
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ISSN | 2169-897X |
EISSN | 2169-8996 |
出版年 | 2018 |
卷号 | 123期号:6页码:3269-3284 |
文章类型 | Article |
语种 | 英语 |
国家 | USA; Italy |
英文摘要 | A number of satellite-based instruments have become an essential part of monitoring emissions. Despite sound theoretical inversion techniques, the insufficient samples and the footprint size of current observations have introduced an obstacle to narrow the inversion window for regional models. These key limitations can be partially resolved by a set of modest high-quality measurements from airborne remote sensing. This study illustrates the feasibility of nitrogen dioxide (NO2) columns from the Geostationary Coastal and Air Pollution Events Airborne Simulator (GCAS) to constrain anthropogenic NOx emissions in the Houston-Galveston-Brazoria area. We convert slant column densities to vertical columns using a radiative transfer model with (i) NO2 profiles from a high-resolution regional model (1x1km(2)) constrained by P-3B aircraft measurements, (ii) the consideration of aerosol optical thickness impacts on radiance at NO2 absorption line, and (iii) high-resolution surface albedo constrained by ground-based spectrometers. We characterize errors in the GCAS NO2 columns by comparing them to Pandora measurements and find a striking correlation (r>0.74) with an uncertainty of 3.5x10(15)moleculescm(-2). On 9 of 10 total days, the constrained anthropogenic emissions by a Kalman filter yield an overall 2-50% reduction in polluted areas, partly counterbalancing the well-documented positive bias of the model. The inversion, however, boosts emissions by 94% in the same areas on a day when an unprecedented local emissions event potentially occurred, significantly mitigating the bias of the model. The capability of GCAS at detecting such an event ensures the significance of forthcoming geostationary satellites for timely estimates of top-down emissions. |
英文关键词 | inverse modeling Kalman filter GCAS remote sensing NOx emissions |
领域 | 气候变化 |
收录类别 | SCI-E |
WOS记录号 | WOS:000430108900020 |
WOS关键词 | SATELLITE NO2 ; DECADAL CHANGES ; OZONE ; RETRIEVAL ; ASSIMILATION ; REFLECTANCE ; INVERSION ; HOUSTON ; MODELS ; O-3 |
WOS类目 | Meteorology & Atmospheric Sciences |
WOS研究方向 | 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/32976 |
专题 | 气候变化 |
作者单位 | 1.Univ Houston, Dept Earth & Atmospher Sci, Houston, TX 77004 USA; 2.Univ Aquila, CETEMPS, Laquila, Italy; 3.Univ Aquila, Dept Phys & Chem Sci, Laquila, Italy; 4.Harvard Smithsonian Ctr Astrophys, 60 Garden St, Cambridge, MA 02138 USA; 5.NASA, Goddard Space Flight Ctr, Code 661, Greenbelt, MD 20771 USA; 6.USRA, Goddard Earth Sci Technol & Res, Greenbelt, MD USA; 7.CALTECH, Jet Prop Lab, Pasadena, CA USA; 8.Univ Maryland Baltimore Cty, Joint Ctr Earth Syst Technol, Baltimore, MD 21228 USA; 9.Natl Ctr Atmospher Res, POB 3000, Boulder, CO 80307 USA |
推荐引用方式 GB/T 7714 | Souri, Amir H.,Choi, Yunsoo,Pan, Shuai,et al. First Top-Down Estimates of Anthropogenic NOx Emissions Using High-Resolution Airborne Remote Sensing Observations[J]. JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES,2018,123(6):3269-3284. |
APA | Souri, Amir H..,Choi, Yunsoo.,Pan, Shuai.,Curci, Gabriele.,Nowlan, Caroline R..,...&Weinheimer, Andrew J..(2018).First Top-Down Estimates of Anthropogenic NOx Emissions Using High-Resolution Airborne Remote Sensing Observations.JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES,123(6),3269-3284. |
MLA | Souri, Amir H.,et al."First Top-Down Estimates of Anthropogenic NOx Emissions Using High-Resolution Airborne Remote Sensing Observations".JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES 123.6(2018):3269-3284. |
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