Comparison of Gaussian and Lagrangian puff Dispersion Models for the Risk Assessment of Receptors Nearby A Contaminated Site

Comparison of Gaussian and Lagrangian puff Dispersion Models for the Risk Assessment of Receptors Nearby A Contaminated Site

Marco Ravina Iason Verginelli Renato Baciocchi Mariachiara Zanetti

Department of Environment, Land and Infrastructure Engineering, Turin Polytechnic, Italy

Department of Civil Engineering and Computer Science, University of Rome “Tor Vergata”, Italy

260 - 270
Available online: 
| Citation



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


[1] Magaril, E., Magaril, R., Panepinto, D., Genon, G., Ravina, M., Trushkova, L. & ChiaraZanetti, M., Production and utilization of energy and climate adaptation: global tasksand local routes. Int. J. SDP, 12, pp. 1326–1337, 2017.

[2] Ravina, M., Panepinto, D. & Zanetti, M., Air quality planning and the minimizationof negative externalities. Resources, 8, p. 15, 2019.

[3] WHO World Health Organization. Contaminated site and health. Report, 2013.

[4] Anenberg, S. C., Belova, A., Brandt, J., Fann, N., Greco, S., Guttikunda, S., Heroux,M.-E., Hurley, F., Krzyzanowski, M., Medina, S., et al., Survey of Ambient Air PollutionHealth Risk assessment tools: Survey of Ambient Air Pollution Health Risk AssessmentTools. Risk Analysis, 36, pp. 1718–1736, 2016.

[5] Ravina, M., Facelli, A. & Zanetti, M., Halocarbon emissions from hazardous wastelandfills: analysis of sources and risks. Atmosphere, 11, p. 375, 2020.

[6] ASTM E2081−00 (2015). Standard guide for risk-based corrective action.

[7] Verginelli, I. ,& Baciocchi, R., Role of natural attenuation in modeling the leaching ofcontaminants in the risk analysis framework. Journal of Environmental Management,114, pp. 395–403, 2013.

[8] U.S. Environmental Protection Agency (US EPA) (2011), CALPUFF modeling systemuser’s manual, version 6.

[9] Briggs, G.A., Diffusion estimates for small emissions (draft). Air Resources AtmosphericTurbulence and Diffusion Laboratory, ATOL No. 79, 1973.

[10] Verginelli, I., Risk-net User Guide. Version 3.1.1. Italy: Reconnet, 2019.

[11] U.S.EPA. Toxicity and chemical/physical properties for Regional screening level (RSL)of chemical Contaminants at Superfund sites, U.S. Environmental Protection Agency,Region 9, May 2020.

[12] Verginelli, I., Nocentini, M. & Baciocchi, R., An alternative screening model for theestimation of outdoor air concentration at large contaminated sites. Atmospheric Environment,165, pp. 349–358, 2017.