Air sparging remediation of VOCs contaminated low-permeability soil based on pressure gradient control

被引:1
|
作者
Xu L. [1 ]
Zhu H. [1 ]
Zha F. [1 ]
Kang H. [2 ]
Fang L. [2 ]
Liu J. [1 ,3 ]
Tan X. [1 ]
Chu C. [1 ]
机构
[1] School of Resource and Environmental Engineering, Hefei University of Technology, Hefei
[2] Tianjin Bochuan Geotechnical Engineering Co., Ltd., Tianjin
[3] Anhui Urban Construction Design Institute Corp., Ltd., Hefei
基金
中国国家自然科学基金;
关键词
Air sparging; Low-permeability soil; Pressure gradient; Remediation efficiency; Volatile organic compounds;
D O I
10.1016/j.chemosphere.2023.139650
中图分类号
学科分类号
摘要
Air sparging (AS) is deemed unacceptable for remediating VOCs contaminated soil with low-permeability. To improve air flow and contaminant removal in sparging process, an original approach, termed as pressure gradient-enhanced air sparging (PGEAS) approach, is proposed by controlling pressure gradient in soil. Then the remediation efficiency, mass transfer characteristics, and remediation mechanism are investigated. Results showed that, the PGEAS approach accelerates gaseous contaminant exhaust, reduces residue contamination in soil, and promotes total contaminant removal, finally results in an improved remediation efficiency compared to the conventional approach. Controlled by sparging pressure and flow distance, the pressure gradient is created in soil, and a critical value needs to be exceeded to enhance the VOCs removal and mass transfer characteristics. The measured results of pore pressure and liquid saturation confirm a notable pressure gradient and drainage behavior in soil, which indicate the massive air subchannel formation during air sparging. At a two-dimensional scale, discrete distributions of contaminant concentrations in exhaust air and soil are presented, the removal extent and area are both enhanced using the PGEAS approach with a pressure gradient higher than the critical value. The reached conclusions are of great importance to contaminant removal in heterogeneous stratigraphy at sites. © 2023 Elsevier Ltd
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