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. Citation statistics:
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