Numerical modeling and performance evaluation of passive convergence-permeable reactive barrier (PC-PRB)

doi:10.1007/s11783-023-1731-z

Front. Environ. Sci. Eng.

2023, Vol. 17

Issue (11) : 131 https://doi.org/10.1007/s11783-023-1731-z

RESEARCH ARTICLE

Numerical modeling and performance evaluation of passive convergence-permeable reactive barrier (PC-PRB)

Kaixuan Zheng¹, Dong Xie¹, Yiqi Tan¹, Zhenjiang Zhuo¹, Tan Chen², Hongtao Wang¹(

), Ying Yuan³(

), Junlong Huang¹, Tianwei Sun¹, Fangming Xu¹, Yuecen Dong¹, Ximing Liang¹

¹. School of Environment, Tsinghua University, Beijing 100084, China
². College of Life and Environmental Sciences, Minzu University of China, Beijing 100081, China
³. State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China

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Abstract

● A 2D finite-element solute transport model, PRB-Trans, is developed.

● PC-PRB can significantly improve the remediation efficiency of PRB.

● PC-PRB can considerably reduce the required PRB dimensions and materials costs.

● The required PRB length decreases with the increase of pipe length, L _p.

The passive convergence-permeable reactive barrier (PC-PRB) was proposed to address the limitations of traditional PRB configurations. To evaluate the hydraulic and pollutant removal performance of the PC-PRB system, we developed a simulation code named PRB-Trans. This code uses the two-dimensional (2D) finite element method to simulate groundwater flow and solute transport. Case studies demonstrate that PC-PRB technology is more efficient and cost-effective than continuous permeable reactive barrier (C-PRB) in treating the same contaminated plume. Implementation of PC-PRB technology results in a 33.3% and 72.7% reduction in PRB length (L_PRB) and height (H_PRB), respectively, while increasing 2D horizontal and 2D vertical pollutant treatment efficiencies of PRB by 87.8% and 266.8%, respectively. In addition, the PC-PRB technology has the ability to homogenize the pollutant concentration and pollutant flux through the PRB system, which can mitigate the problems arising from uneven distribution of pollutants in the C-PRB to some extent. The L_PRB required for PC-PRB decreases as the water pipe length (L_p) increases, while the H_PRB required initially decreases and then increases with increasing L_p. The effect of passive well height (H_w) on H_PRB is not as significant as that of L_p on H_PRB. Overall, PC-PRB presents a promising and advantageous PRB configuration in the effective treatment of various types of contaminated plumes.

Keywords Passive convergence-permeable reactive barrier Numerical modeling Hydraulic behavior assessment Pollutant treatment performance evaluation Influential factors analysis

Corresponding Author(s): Hongtao Wang,Ying Yuan

Issue Date: 15 November 2023

Cite this article:

Kaixuan Zheng,Dong Xie,Yiqi Tan, et al. Numerical modeling and performance evaluation of passive convergence-permeable reactive barrier (PC-PRB)[J]. Front. Environ. Sci. Eng., 2023, 17(11): 131.

URL:

https://academic.hep.com.cn/fese/EN/10.1007/s11783-023-1731-z
https://academic.hep.com.cn/fese/EN/Y2023/V17/I11/131

Fig.1 A schematic diagram of the PC-PRB system (Zheng et al., 2022b).

Fig.2 Representation of the main PC-PRB design parameters in the PRB-Trans code. (a) The horizontal 2D confined aquifer, (b) the vertical 2D confined aquifer.

Tab.1 Geometric parameters and their values of the PC-PRB and C-PRB

Tab.2 Definitions and estimation methods of the performance evaluation indicators

Fig.3 Comparison of pollutant concentration distribution in plumes treated with PC-PRB and C-PRB. (a) The horizontal 2D pollutant concentration distribution of plume treated with C-PRB (L_PRB = 54 m), (b) the horizontal 2D pollutant concentration distribution of plume treated with PC-PRB (L_PRB = 36 m), (c) the vertical 2D pollutant concentration distribution of plume treated with C-PRB (H_PRB = 22 m), and (d) the vertical 2D pollutant concentration distribution of plume treated with PC-PRB (H_PRB = 6 m).

Tab.3 Comparison between the horizontal 2D performance evaluation indicators of the PC-PRB and those of the PRB (at t = 3000 d)

Tab.4 Comparison between the vertical 2D performance evaluation indicator of the PC-PRB and those of the PRB (at t = 3000 d)

Fig.4 Effect of L_p at three width levels of plumes on: (a) ΔL_PRB, (b) ΔQ_h, (c) ΔW_h, (d) ΔF_h, (e) ΔC_h, (f) Δq_h, (g) Δw_h, (h) Δf_h, (i) Δt_h.

Fig.5 Effect of L_p at three depth levels of plumes on: (a) ΔH_PRB, (b) ΔQ_v, (c) ΔW_v, (d) ΔF_v, (e) ΔC_v, (f) Δq_v, (g) Δw_v, (h) Δf_v, (i) Δt_v.

Fig.6 Effect of H_w at three depth levels of plumes on: (a) ΔH_PRB, (b) ΔQ_v, (c) ΔW_v, (d) ΔF_v, (e) ΔC_v, (f) Δq_v, (g) Δw_v, (h) Δf_v, (i) Δt_v.

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[1]	Kaixuan Zheng, Xingshen Luo, Yiqi Tan, Zhonglei Li, Hongtao Wang, Tan Chen, Li Zhao, Liangtong Zhan. Passive convergence-permeable reactive barrier (PC-PRB): An effective configuration to enhance hydraulic performance[J]. Front. Environ. Sci. Eng., 2022, 16(12): 156-.

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