Source reconstruction of an accidental radionuclide release at European scale

Krysta, Monika; Bocquet, Marc

doi:10.1002/qj.3

Cited by 40 publications

(39 citation statements)

References 26 publications

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“…The method was later extended (Bocquet, 2005a;Krysta and Bocquet, 2007) to statistically consistent diagnostic tools to estimate a posteriori the quality of a reconstruction. It has several advantages such as the fact that the cost function that is built is always convex.…”

Section: Non-gaussian Approachesmentioning

confidence: 99%

“…The method was then successfully applied to the real data of the Euporean Tracer Experiments [ETEX] (Bocquet, 2007;Krysta et al, 2007) with a view to a high-resolution reconstruction of the source. The source was correctly localised (ETEX-I and ETEX-II), and the total released mass was correctly estimated up to a few percents (ETEX-I).…”

Section: Non-gaussian Approachesmentioning

confidence: 99%

“…√ χ is chosen optimally by an L-curve a posteriori analysis and confirmed by a maximum likelihood estimation, in a sense defined elsewhere (Davoine and Bocquet, 2007;Krysta et al, 2007) to be √ χ=0.3 ng m −3 . The first source prior is Gaussian, without bias and with a background diagonal covariance matrix given by B=m 2 I .…”

Section: Application Setupmentioning

confidence: 99%

“…(This conventional λ 2 factor differs from the not less conventional λ Gaussian factor because of scaling arguments on prior statistics.) Note that this time, m and √ χ do not represent the same degree of freedom, so that they have been jointly estimated by iterative L-curve techniques following (Davoine and Bocquet, 2007;Krysta et al, 2007). Both priors have been chosen because they illustrate the main differences between a reconstruction based on Gaussian and non-Gaussian hypotheses.…”

Section: Application Setupmentioning

confidence: 99%

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Inverse modelling of atmospheric tracers: non-Gaussian methods and second-order sensitivity analysis

Bocquet

2008

Nonlin. Processes Geophys.

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Abstract. For a start, recent techniques devoted to the reconstruction of sources of an atmospheric tracer at continental scale are introduced. A first method is based on the principle of maximum entropy on the mean and is briefly reviewed here. A second approach, which has not been applied in this field yet, is based on an exact Bayesian approach, through a maximum a posteriori estimator. The methods share common grounds, and both perform equally well in practice. When specific prior hypotheses on the sources are taken into account such as positivity, or boundedness, both methods lead to purposefully devised cost-functions. These cost-functions are not necessarily quadratic because the underlying assumptions are not Gaussian. As a consequence, several mathematical tools developed in data assimilation on the basis of quadratic cost-functions in order to establish a posteriori analysis, need to be extended to this nonGaussian framework. Concomitantly, the second-order sensitivity analysis needs to be adapted, as well as the computations of the averaging kernels of the source and the errors obtained in the reconstruction. All of these developments are applied to a real case of tracer dispersion: the European Tracer Experiment [ETEX]. Comparisons are made between a least squares cost function (similar to the so-called 4D-Var) approach and a cost-function which is not based on Gaussian hypotheses. Besides, the information content of the observations which is used in the reconstruction is computed and studied on the application case. A connection with the degrees of freedom for signal is also established. As a byproduct of these methodological developments, conclusions are drawn on the information content of the ETEX dataset as seen from the inverse modelling point of view.

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Section: Non-gaussian Approachesmentioning

confidence: 99%

Section: Non-gaussian Approachesmentioning

confidence: 99%

Section: Application Setupmentioning

confidence: 99%

Section: Application Setupmentioning

confidence: 99%

See 2 more Smart Citations

Inverse modelling of atmospheric tracers: non-Gaussian methods and second-order sensitivity analysis

Bocquet

2008

Nonlin. Processes Geophys.

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“…However, it is often required to derive new adjoint operators corresponding to the gradient of the cost function with respect to these parameters if the driving mechanisms are not external forcings. Often, adjoint models and operators can nonetheless be obtained through a simplifying approximation (Issartel and Baverel, 2003;Krysta and Bocquet, 2007;Bocquet, 2012;Singh and Sandu, 2012).…”

Section: From State Estimation To Physical Parameter Estimationmentioning

confidence: 99%

Data assimilation in atmospheric chemistry models: current status and future prospects for coupled chemistry meteorology models

et al. 2015

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Abstract. Data assimilation is used in atmospheric chemistry models to improve air quality forecasts, construct re-analyses of three-dimensional chemical (including aerosol) concentrations and perform inverse modeling of input variables or model parameters (e.g., emissions). Coupled chemistry meteorology models (CCMM) are atmospheric chemistry models that simulate meteorological processes and chemical transformations jointly. They offer the possibility to assimilate both meteorological and chemical data; however, because CCMM are fairly recent, data assimilation in CCMM has been limited to date. We review here the current status of data assimilation in atmospheric chemistry models with a particular focus on future prospects for data assimilation in CCMM. We first review the methods available for data assimilation in atmospheric models, including variational methods, ensemble Kalman filters, and hybrid methods. Next, we review past applications that have included chemical data assimilation in chemical transport models

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Reconstruction of an atmospheric tracer source in an urban‐like environment

et al. 2015

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This study describes a methodology combining a recently proposed renormalization inversion technique with a building‐resolving computational fluid dynamics (CFD) approach for source retrieval in the geometrically complex urban regions. It presents the first application of the renormalization inversion approach to estimate an unknown continuous point release in real situations at an urban scale. The renormalization inversion approach is based on an adjoint source‐receptor relationship and is purely deterministic in nature. The source parameters (i.e., source location and release rate) are reconstructed from a finite set of point measurements of concentration acquired from some sensors and the adjoint functions computed from a CFD model fluidyn‐PANACHE that is able to represent the geometric and flow complexity inherent in the urban regions. The inversion procedure is evaluated for a point source reconstruction using measurements from the Mock Urban Setting Test (MUST) field experiment. Source reconstructions are performed for 20 trials of the MUST experiment of a continuous point release in an idealized urban geometry consisting of a regular array of shipping containers. The steady state flow fields are computed by solving the three‐dimensional Reynolds‐averaged Navier‐Stokes equations by using a finite volume scheme. Then, in each MUST trial adjoint functions are obtained and used for the source identification. Inversion results are presented with both synthetic and real measurements in various atmospheric stabilities varying from neutral to stable and very stable conditions. With real concentration measurements, the point source is retrieved within an average Euclidean distance of 14.6 m from the actual source location. The estimated source intensity is overpredicted by an average factor of 1.37 of the true release rate. In a posterior uncertainty analysis with 10% random noise in measurements, it is demonstrated that standard deviation in the location error and release strength, respectively, varies by 5.22 m and ∼21% from their mean value for all 20 trials. A sensitivity analysis shows that the use of nonzero measurements helps in reducing the uncertainties involved in the source reconstruction. The source reconstruction results in various stability conditions exhibit the reliability of the renormalization inversion methodology coupled with the CFD approach in an urban area. The present methodology can be used by emergency regulators as a tool to detect the unknown accidental or deliberated releases in the complex urban environments.

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Source reconstruction of an accidental radionuclide release at European scale

Cited by 40 publications

References 26 publications

Inverse modelling of atmospheric tracers: non-Gaussian methods and second-order sensitivity analysis

Inverse modelling of atmospheric tracers: non-Gaussian methods and second-order sensitivity analysis

Data assimilation in atmospheric chemistry models: current status and future prospects for coupled chemistry meteorology models

Reconstruction of an atmospheric tracer source in an urban‐like environment

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