WIT Press

Comparison of Gaussian and Lagrangian puff dispersion models for the risk assessment of receptors nearby a contaminated site


Free (open access)


Volume 10 (2022), Issue 3



Page Range

260 - 270

Paper DOI



WIT Press


Marco Ravina, Iason Verginelli, Renato Baciocchi & Mariachiara Zanetti


Human health risk assessment for off-site receptors located in the proximity of a contaminated site is based on the application of pollutant atmospheric dispersion models. In the standard ASTM Risk-Based Corrective Action (RBCA-ASTM) procedure, this evaluation is carried out by coupling a one-dimensional Gaussian dispersion model to a simple dilution box model. In this work, the accuracy of this approach is examined by comparing the output obtained by the standard Gaussian box model with the results obtained with the non-steady-state Lagrangian puff dispersion model CALPUFF. A case study was considered, assuming the emission of benzene from a contaminated area of 200 × 200 m on flat terrain. The comparison of concentration profiles as a function of the distance from the source showed that the standard procedure overestimated concentrations by more than one order of magnitude. Two possible refinements to the standard RBCA-ASTM procedure were suggested. The first is the introduction of an equivalent mixing height for the application of the box model, calculated on the basis of the atmospheric stability class, land use typology, and dimension of the source. The second is the consideration of the wind distribution of the area. The introduction of these modifications allowed to reduce the discrepancy between the Gaussian box model and CALPUFF. This study also showed that the use of advanced dispersion models integrated with the risk calculation methodologies, allowed a detailed characterization of the risk in the area under examination, highlighting the most critical areas and comparing them with the presence of any sensitive receptors.


atmospheric dispersion modelling, concentration exposure, contaminated site, human health risk assessment.