DOI: 10.1016/j.atmosenv.2015.08.063
Scopus记录号: 2-s2.0-84940530297
论文题名: Assimilation of concentration measurements for retrieving multiple point releases in atmosphere: A least-squares approach to inverse modelling
作者: Singh S ; K ; , Rani R
刊名: Atmospheric Environment
ISSN: 0168-2563
EISSN: 1573-515X
出版年: 2015
卷: 119 起始页码: 402
结束页码: 414
语种: 英语
英文关键词: Data assimilation
; Fusion field trials
; Least-squares
; Multiple releases
; Source reconstruction
Scopus关键词: Dispersions
; Data assimilation
; Field trial
; Least Square
; Multiple release
; Source reconstruction
; Location
; algorithm
; atmospheric modeling
; atmospheric pollution
; concentration (composition)
; data assimilation
; least squares method
; model validation
; point source pollution
; pollution monitoring
; reconstruction
; tracer
; algorithm
; Article
; atmosphere
; atmospheric dispersion
; concentration (parameters)
; cost minimization analysis
; filtration
; methodology
; normal distribution
; priority journal
; regression analysis
; uncertainty
; United States
; Utah
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: The study addresses the identification of multiple point sources, emitting the same tracer, from their limited set of merged concentration measurements. The identification, here, refers to the estimation of locations and strengths of a known number of simultaneous point releases. The source-receptor relationship is described in the framework of adjoint modelling by using an analytical Gaussian dispersion model. A least-squares minimization framework, free from an initialization of the release parameters (locations and strengths), is presented to estimate the release parameters. This utilizes the distributed source information observable from the given monitoring design and number of measurements. The technique leads to an exact retrieval of the true release parameters when measurements are noise free and exactly described by the dispersion model. The inversion algorithm is evaluated using the real data from multiple (two, three and four) releases conducted during Fusion Field Trials in September 2007 at Dugway Proving Ground, Utah. The release locations are retrieved, on average, within 25-45 m of the true sources with the distance from retrieved to true source ranging from 0 to 130 m. The release strengths are also estimated within a factor of three to the true release rates. The average deviations in retrieval of source locations are observed relatively large in two release trials in comparison to three and four release trials. © 2015 Elsevier Ltd. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/81572
Appears in Collections: 气候变化事实与影响
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作者单位: LMEE, Universite d'Evry-Val d'Essonne, 40 Rue Du Pelvoux, Courcouronnes, France; Centre for Atmospheric Sciences, IIT Delhi, Hauz Khas, New Delhi, India
Recommended Citation:
Singh S,K,, Rani R. Assimilation of concentration measurements for retrieving multiple point releases in atmosphere: A least-squares approach to inverse modelling[J]. Atmospheric Environment,2015-01-01,119