Determination of major pollutant and biogeochemical processes in an oil-contaminated aquifer using human health risk assessment and multivariate statistical analysis

ABSTRACT

Techniques for monitored natural attenuation usually produce large complex datasets that are difficult to interpret. Here, human health risk assessments and multivariate statistical analyses are combined to extract and analyze useful information from large monitoring datasets to identify the main pollutants in a petroleum-contaminated aquifer in northeast China and the main biogeochemical processes affecting the pollutants. The data included organic and inorganic geochemical species concentrations, physicochemical indicators, C and S stable isotope data collected for four years of more than 10 monitoring. The health risk assessment indicated that benzene was a representative pollutant. Cluster analysis classified the groundwater samples into two groups and indicated strong biodegradation occurred near the core and upgradient of the petroleum hydrocarbon plume. The factors explaining most variability were extracted by principal component analysis, which correlated with biodegradation and mineral dissolution processes. The factor scores and spatial distributions of hydrogeochemical and isotope indicators confirmed that biodegradation effects weakened and mineral dissolution strengthened upgradient to downgradient of the contaminated plume. The analysis method could be useful for rapidly studying pollution characteristics and identifying biodegradation processes in contaminated aquifersfrom large complex datasets. The results will provide a basis for developing an enhanced bioremediation scheme for the study site.

KEYWORDS:

• human health risk assessment
• multivariate statistical analysis
• groundwater
• petroleum hydrocarbon contamination
• biodegradation

Acknowledgments

We would like to express our sincere thanks to the editor and the anonymous reviewers for the constructive and positive advice and comments which helped improve the manuscript.

Disclosure of potential conflicts of interest

The authors declare that they have no competing interests.

Additional information

Funding

This work is supported by the project funded by National Natural Science Foundation of China (41702252), China Postdoctoral Science Foundation (149194) and Open Foundation of Engineering Research Center of Geothermal Resources Development Technology and Equipment, Ministry of Education, Jilin University.