Emergence of a tracer source from air concentration measurements, a new strategy for linear assimilation

Issartel, Jean-Pierre

doi:10.5194/acp-5-249-2005

Cited by 44 publications

(77 citation statements)

References 30 publications

(34 reference statements)

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“…The renormalization technique has already been tested, and found to be working efficiently, with the concentration measurements obtained from dispersion experiments at local [Sharan et al, 2009[Sharan et al, , 2012 and continental [Issartel, 2005, Issartel et al, 2007 scales. Since the ultimate proof for any STE algorithms is the practical validation, the discrete renormalization method has to be ''tested'' and ''validated'' against new…”

Section: Resultsmentioning

confidence: 99%

“…Issartel [2005] showed that a unique weight function f ðxÞ5uðxÞ best avoiding inversion artifacts exists. This function is optimal in the sense that it minimizes the excess entropy.…”

Section: An Appropriate Weight Function To Minimize Artificial Informmentioning

confidence: 99%

“…Such a problem is necessarily addressed by use of a model which describes our understanding of the relationship between the concentration measurements, the known parameters of the problem (meteorological data, variables characterizing the atmospheric domain and the receptors…), and the source parameters that we wish to estimate. In the approach proposed by Issartel [2005], a receptor oriented (also designated as backward) model is used to establish a mapping between the problem parameters and the measured data. The n actual measured concentrations are assembled into an observation vector l 2 R n (bold-face, lower-case letters refer to vectors, and italic lower-case letters refer to vector components or scalar).…”

Section: Inverse Problem Statementmentioning

confidence: 99%

“…This approach has been defined by Issartel [2005] to reconstruct tracer source from air concentration measurements at continental scale only using measured data. It relies on the networking of several detectors, on the use of adjoint transport equations (inverse modeling methods) and on the computation of a renormalizing weight function (also referred to as the visibility function).…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Reconstructing source terms from atmospheric concentration measurements: Optimality analysis of an inversion technique

Turbelin

Singh

Issartel³

2014

J Adv Model Earth Syst

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In the event of an accidental or intentional contaminant release in the atmosphere, it is imperative, for managing emergency response, to diagnose the release parameters of the source from measured data. Reconstruction of the source information exploiting measured data is called an inverse problem. To solve such a problem, several techniques are currently being developed. The first part of this paper provides a detailed description of one of them, known as the renormalization method. This technique, proposed by Issartel (2005), has been derived using an approach different from that of standard inversion methods and gives a linear solution to the continuous Source Term Estimation (STE) problem. In the second part of this paper, the discrete counterpart of this method is presented. By using matrix notation, common in data assimilation and suitable for numerical computing, it is shown that the discrete renormalized solution belongs to a family of well-known inverse solutions (minimum weighted norm solutions), which can be computed by using the concept of generalized inverse operator. It is shown that, when the weight matrix satisfies the renormalization condition, this operator satisfies the criteria used in geophysics to define good inverses. Notably, by means of the Model Resolution Matrix (MRM) formalism, we demonstrate that the renormalized solution fulfils optimal properties for the localization of single point sources. Throughout the article, the main concepts are illustrated with data from a wind tunnel experiment conducted at the Environmental Flow Research Centre at the University of Surrey, UK.

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Section: Resultsmentioning

confidence: 99%

“…Issartel [2005] showed that a unique weight function f ðxÞ5uðxÞ best avoiding inversion artifacts exists. This function is optimal in the sense that it minimizes the excess entropy.…”

Section: An Appropriate Weight Function To Minimize Artificial Informmentioning

confidence: 99%

Section: Inverse Problem Statementmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Reconstructing source terms from atmospheric concentration measurements: Optimality analysis of an inversion technique

Turbelin

Singh

Issartel³

2014

J Adv Model Earth Syst

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“…The superscript T denotes the transposition. In order to eliminate the singularities of the adjoint functions and minimize all inversion artefacts, the weight function ϕ(x, y) is chosen in such a way that (Issartel, 2005) …”

Section: Renormalizationmentioning

confidence: 99%

A point‐source reconstruction from concentration measurements in low‐wind stable conditions

Sharan¹,

Issartel

Singh³

2012

Quart J Royal Meteoro Soc

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An inversion technique is proposed to reconstruct an elevated point emission source of known height of atmospheric trace species from a finite number of concentration measurements in low-wind stable conditions. Observations from the SF 6 diffusion experiment at Idaho National Engineering Laboratory in low-wind stable conditions are used for the point source reconstruction.The source location and its strength are both retrieved exactly with the modelgenerated measurements in all the runs. With real data, the location is reconstructed with an average error of 20 m, mostly along the wind, and the intensity is retrieved within a factor of 2 in all the runs. The incurred errors in the retrieval are justified by estimating the angular departure between the vectors of measurement and adjoint function. A sensitivity study is carried out to analyse the sensitivity of the source estimation with respect to signal perturbation caused by the background concentration of the species in the ambient air. Source reconstruction is shown to be improved and more focused when the samplers having a measurement value corresponding to the background concentration are maintained in the inversion process. Copyright c 2012 Royal Meteorological SocietyKey Words: data assimilation; elevated source; inverse modelling; retrieval errors; weak winds; wind variability Citation: Sharan M, Issartel J-P, Singh SK. A point-source reconstruction from concentration measurements in low-wind stable conditions. Q.

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Reconstruction of an atmospheric tracer source in Fusion Field Trials: Analyzing resolution features

et al. 2015

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Reconstruction of unknown atmospheric releases using measured concentrations is an ill-posed inverse problem. Due to insufficient measurements and dispersion model uncertainties, reliable interpretation of a retrieved source is limited by lack of resolution, nonuniqueness, and instability in the inverse solution. The study presents an optimality analysis, in terms of resolution, stability, and reliability, of an inverse solution given by a recently proposed inversion technique, called as renormalization. The inversion technique is based on an adjoint source-receptor framework and construction of a weight function which interprets a priori information about the unknown release apparent to the monitoring network. The properties of weight function provide a perfect data resolution, maximum model resolution, and minimum variance (or stability) for the retrieved source. The reliability of the retrieved source is interpreted in view of the information derived from the geometry of the monitoring network. The inversion technique and resolution features are evaluated for a point source reconstruction using measurements from a recent dispersion experiment (Fusion Field Trials 2007) conducted at Dugway Proving Ground, Utah. With the real measurements, the point release is reconstructed within an average distance of 23 m from the true release where the average distance of the nearest receptor from the true source was 32 m. In all the trials, the point release is retrieved within 3-60 m Euclidean distance from their true location. The source strength is retrieved within a factor of 1.5 to the true release mass. The posterior uncertainty in the release parameters is observed to be within 20% of their mean value. The source localization features are resolved to its maximum extent feasible with the design of the monitoring network. The sensitivity studies are conducted to highlight the importance of receptors reporting zero concentration measurements and variations in the resolution features of the source retrieval with respect to the various arrangements of the receptors.

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Emergence of a tracer source from air concentration measurements, a new strategy for linear assimilation

Cited by 44 publications

References 30 publications

Reconstructing source terms from atmospheric concentration measurements: Optimality analysis of an inversion technique

Reconstructing source terms from atmospheric concentration measurements: Optimality analysis of an inversion technique

A point‐source reconstruction from concentration measurements in low‐wind stable conditions

Reconstruction of an atmospheric tracer source in Fusion Field Trials: Analyzing resolution features

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