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Contributed Articles

Forensic analytical approach for hydrocarbon fingerprinting in soil vapor samplings: Example of a residential neighborhood in Brazil

ORCID Icon, , , &
Pages 93-113 | Published online: 08 Mar 2021
 

Abstract

Conventional analytical methods determine the concentration of compounds used to estimate the presence of environmental contamination capable of posing risk to human and ecological receptors. While these target analytes help regulators and environmental professional identify and manage potentially harmful conditions, these compounds can be generated by many natural and anthropogenic (man-made) sources and conventional methods alone fail to compositionally differentiate subsurface sources of contamination in complex environments. This case study demonstrates the advantage of using both conventional and forensic testing methods to accurately identify the source(s) of volatile hydrocarbon contamination in soil vapor samples for the development of an accurate conceptual site model in a neighbourhood near industrial facilities in Rio de Janeiro State, Brazil. The goal of this study was to differentiate potential impacts from a local steelmaking plant from fugitive hydrocarbons associated with more generic human activity in urban settings. This case study demonstrated the advantage of constructing chemical fingerprints from conventional volatile organic compound (VOC) method TO 15 and a forensic volatile hydrocarbon method using an enhanced version of method TO 15 (PIANO). The chemical fingerprints of vapor samples collected from subsurface soil gas and sewers were analysed and compared to laboratory reference samples. These data determined that the VOCs detected in neighbourhood soil vapor samples were associated with fugitive petroleum products migrating in the sewer pipelines and not with the steelmaking wastes emplaced near the residential area. This article discusses the forensic data and chemical signatures that support these findings, and the use of environmental forensic techniques to evaluate environmental data associated with complex scenarios, involving multiple contamination sources.

Acknowledgements

We thank our colleagues from New Fields (Rio de Janeiro and Boston offices), to Craig A. Cox and Laurie Chilcote from Cox-Colvin & Associates, Inc. and to CEPAS (Groundwater Research Center of the Institute of Geosciences, University of Sao Paulo), in particular to Sasha Tom Hart, who provided insight and expertise that greatly assisted the research.

Conflicts of interest

The authors declare no conflicts of interest regarding the publication of this paper.

Additional information

Funding

This work was supported by CSN—Companhia Siderúrgica Nacional.

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