Using dynamic flux chambers to estimate the natural attenuation rates in the subsurface at petroleum contaminated sites

Abstract

In this work, we introduce a screening method for the evaluation of the natural attenuation rates in the subsurface at sites contaminated by petroleum hydrocarbons. The method is based on the combination of the data obtained from standard source characterization with dynamic flux chambers measurements. The natural attenuation rates are calculated as difference between the flux of contaminants estimated with a non-reactive diffusive model starting from the concentrations of the contaminants detected in the source (soil and/or groundwater) and the effective emission rate of the contaminants measured using dynamic flux chambers installed at ground level. The reliability of this approach was tested in a contaminated site characterized by the presence of BTEX in soil and groundwater. Namely, the BTEX emission rates from the subsurface were measured in 4 seasonal campaigns using dynamic flux chambers installed in 14 sampling points. The comparison of measured fluxes with those predicted using a non-reactive diffusive model, starting from the source concentrations, showed that, in line with other recent studies, the modelling approach can overestimate the expected outdoor concentration of petroleum hydrocarbons even up to 4 orders of magnitude. On the other hand, by coupling the measured data with the fluxes estimated with the diffusive non-reactive model, it was possible to perform a mass balance to evaluate the natural attenuation loss rates of petroleum hydrocarbons during the migration from the source to ground level. Based on this comparison, the estimated BTEX loss rates in the test site were up to almost 0.5kg/year/m2. These rates are in line with the values reported in the recent literature for natural source zone depletion. In short, the method presented in this work can represent an easy-to-use and cost-effective option that can provide a further line of evidence of natural attenuation rates expected at contaminated sites.