首页|Quantifying contamination risks: Groundwater vulnerability assessment at an MSW dumpsite with advanced profiling tools
Quantifying contamination risks: Groundwater vulnerability assessment at an MSW dumpsite with advanced profiling tools
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NETL
NSTL
Elsevier
Traditional groundwater vulnerability assessment methods rely on regional-scale parameters that often overlook local soil variation. They also tend to ignore the contamination potential at already contaminated sites, particularly in heterogeneous environments. This study employs advanced direct push profiling tools to quantify groundwater vulnerability at an MSW dumpsite using real-time hydrogeological and contamination data. A vulnerability score was developed considering waste, unsaturated and saturated zone permeability, water table depth, and the waste bulk electrical conductivity. All parameters were calculated from the cone penetrometer (CPT), direct push injection logger (DPIL) and electrical conductivity (EC) logger profiles. A laboratory and computational validation of DPIL and EC was carried out before the field tests and their capabilities and limitations were discussed in detail. It was concluded that the permeability of MSW was better estimated by the DPIL than CPT due to the presence of construction and demolition waste (C&DW) influencing the CPT values. Conversely, CPT provided more realistic values in the low permeability soils i.e., soils with permeability less than 10-6 m/s, which are beyond the measurable range of DPIL. The bulk EC was a reliable proxy for leachate contamination potential in most cases except in soils with very low water content. The groundwater vulnerability score (GWVS) was calculated for different regions in the landfill with varying subsurface and waste conditions. The boundary region of the landfill had a higher GWVS than the interior region due to the presence of high permeability unsaturated zone, indicating the need for remediation of the entire site. The proposed framework can assist in prioritizing remediation efforts on high-risk zones identified in this study.
NETL
NSTL
Elsevier
