An accurate simulation of the short-range plume dispersion of a hazardous pollutant in a geometrically complex urban region is a prerequisite in emergency preparedness and to assist regulators for developing effective policies. This study critically examines the real predictive capability of a three-dimensional Computational Fluid Dynamics (CFD) model, Fluidyn-PANACHE, to apply it in emergency contexts of an accidental or deliberate three cases of the inflow boundary conditions is well achieved within the acceptable standards for air quality applications. The model with three cases 1, 2, & 3 predicts respectively 52.8%, 59.9%, and 67.9% of the total concentrations within a factor of two and shows an overall under-prediction. The sampling line maximum concentrations are better simulated by the CFD model with case-3 (95% within a factor of two) in comparison to other cases 1 & 2. A comparative statistical analysis is also performed with other evaluation studies in the literature for the averaged and sampling line maximum concentrations. The present evaluation of the Fluidyn-PANACHE strengthen the evidence that it is capable of dealing properly with the dispersion phenomena in geometrically complex urban environments.

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.

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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This study illustrates an atmospheric source reconstruction methodology for identification of an unknown continuous point release in the geometrically complex urban environments. The methodology is based on the renormalization inversion theory coupled with a building resolving Computational Fluid Dynamics (CFD) modelling approach which estimates the release height along with the projected location on the ground surface and the intensity of an unknown continuous point source in an urban area. An estimation of the release height in a three-dimensional urban environment is relatively more difficult from both technical and computational point of view.