globalchange  > 气候变化事实与影响
DOI: 10.1016/j.atmosenv.2013.11.027
Scopus记录号: 2-s2.0-84889588836
论文题名:
Improvement of air quality forecasts with satellite and ground based particulate matter observations
作者: Hirtl M; , Mantovani S; , Krüger B; C; , Triebnig G; , Flandorfer C; , Bottoni M; , Cavicchi M
刊名: Atmospheric Environment
ISSN: 0168-2563
EISSN: 1573-515X
出版年: 2014
卷: 84
起始页码: 20
结束页码: 27
语种: 英语
英文关键词: MODIS AOT ; PM10 forecasts ; Support Vector Regression ; WRF/Chem
Scopus关键词: Air quality ; Forecasting ; Satellite imagery ; Air pollution measurements ; Air quality forecasts ; MODIS AOT ; Particulate air pollution ; Satellite measurements ; Satellite observations ; Support vector regression (SVR) ; WRF/Chem ; Particles (particulate matter) ; aerosol ; air quality ; atmospheric pollution ; forecasting method ; ground-based measurement ; interpolation ; MODIS ; real time ; satellite data ; air monitoring ; air pollution ; air quality ; article ; forecasting ; measurement accuracy ; particulate matter ; priority journal ; sensor ; support vector machine
Scopus学科分类: Environmental Science: Water Science and Technology ; Earth and Planetary Sciences: Earth-Surface Processes ; Environmental Science: Environmental Chemistry
英文摘要: Daily regional scale forecasts of particulate air pollution are simulated for public information and warning. An increasing amount of air pollution measurements is available in real-time from ground stations as well as from satellite observations. In this paper, the Support Vector Regression technique is applied to derive highly-resolved PM10 initial fields for air quality modeling from satellite measurements of the Aerosol Optical Thickness.Additionally, PM10-ground measurements are assimilated using optimum interpolation. The performance of both approaches is shown for a selected PM10 episode. © 2013 Elsevier Ltd.
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资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/80845
Appears in Collections:气候变化事实与影响

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作者单位: Section Environmental Meteorology, ZAMG - Central Institute for Meteorology and Geodynamics, Vienna, Austria; SISTEMA GmbH, Vienna, Austria; Institute of Meteorology, BOKU - University of Natural Resources and Life Sciences, Vienna, Austria; EOX IT Services GmbH, Vienna, Austria; MEEO S.r.l., Ferrara, Italy

Recommended Citation:
Hirtl M,, Mantovani S,, Krüger B,et al. Improvement of air quality forecasts with satellite and ground based particulate matter observations[J]. Atmospheric Environment,2014-01-01,84
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