Prediction models for effective PVD-enhanced in-situ flushing remediation of multi-layered soils

• Published in: Computers and geotechnics Vol. 166; p. 106022
• Main Authors: Jiang, Lianghua, Qin, Aifang, Li, Linzhong, Meng, Hongping, Xu, Wei
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01-02-2024
• Subjects: Analytical model; Flushing remediation; Imperfect diffusion boundaries; Matrix analysis; Multi-layered soils; Analytical model; Matrix analysis; Flushing remediation; Imperfect diffusion boundaries; Multi-layered soils
• ISSN: 0266-352X; 1873-7633
• DOI: 10.1016/j.compgeo.2023.106022

The re-utilization of original industrial sites poses a significant challenge in the remediation of contaminated soils, driven by the transformation of urban industrial spaces. In this study, a prediction model is proposed to address this challenge by focusing on the in-situ flushing remediation of multi-layered soils enhanced with PVDs. The analytical model is versatile for various scenarios where the boundaries have different diffusion capacities by introducing imperfect diffusion boundaries. It incorporates the effects of the sandy silt layer and the decay characteristics of initial contaminant concentrations with depth on remediation efficiency of multi-layered contaminated soils. To validate the model, the solutions derived from the matrix analysis were compared with experimental data and numerical simulation results from COMSOL Multiphysics. Parametric analysis reveals that the model effectively captures different boundary conditions ranging from fully non-diffusive to completely diffusive by utilizing the imperfect diffusion capacity coefficient within the range of 0 to 50. Furthermore, the remediation of the upper and lower silty clay layers of the sandy silt layer was different but both decreased in efficiency as the thickness of the sandy silt layer increased. Notably, the concentration of the contaminant exhibits more pronounced variations with increasing radial dispersivity compared to vertical dispersivity.