Monitoring data regarding aqueous groundwater concentrations of chlorinated ethenes and chlorinated methanes as well as ancillary parameters (such as geochemical, nutrient and field data) have been collected from a contaminated site in South America for over a decade.
Chlorinated ethenes and halomethanes are common groundwater pollutants that are subject to various chemical, physical and biological forces and can undergo chemical reactions and transformations. A biotreatment system was recently installed at the site in effort to remediate groundwater contaminated with chlorinated ethenes and halomethanes. Statistical analysis via Positive Matrix Factorization (PMF) was applied to a dataset of concentrations of these organohalides and their degradation products measured in the groundwater. The purpose of this work was to use a new data mining technique to investigate dehalogenation in the subsurface and to assess the efficacy of recent bioremediation efforts at the site.
1.) Apply PMF analysis on groundwater monitoring data for aqueous concentrations of chlorinated ethenes and halomethanes.
2.) Examine temporal and spatial trends of PMF model output for each organohalide contaminant class.
3.) Investigate correlations between PMF outputs related to dehalogenation using available ancillary parameters such as geochemical, nutrient, and field data.
4.) Assess bioremediation activities and make recommendations regarding future efforts.
This novel data mining approach has proven useful in interpreting groundwater monitoring data provided a cohesive dataset. The PMF analysis converged on a stable solution for all data sets and provided insights into the processes occurring in the subsurface. PMF was useful in characterizing different biotreatment locations and revealing biotic (cell-mediated) and abiotic (mineral-mediated) reactions resulting in distinct fingerprints for each organohalide family explored in this work. Provided enough data on ancillary parameters that are indicative of redox conditions in the subsurface, correlating the PMF output with those parameters can suggest the conditions that are conducive to dehalogenation of the different classes of organohalides. Here, this data mining technique revealed conditions that are favorable for dehalogenation of chlorinated ethenes and halomethanes. The advanced dehalogenation regime of chlorinated ethenes was correlated with methanogenic conditions indicating that advanced dehalogenation of chlorinated ethenes is most prevalent in highly reducing environments. In contrast, dehalogenation of carbon tetrachloride and chloroform can occur under lesser reducing conditions (e.g., iron-reducing conditions). Finally, areas with elevated concentrations of carbon tetrachloride and chloroform appeared to inhibit dehalogenation of chlorinated ethenes resulting in vinyl chloride accumulation.