Abstract
Biological clogging in porous media was an important concern in the design of bio-augmented permeable reactive barriers (Bio-PRBs) that were used to remediate groundwater with dense non-aqueous phase liquids (DNAPLs). Here, we used laboratory sandbox experiments to develop and calibrate reactive transport models (C1 and C2) simulating 1,1,1-trichloroethane (1,1,1-TCA) change in heterogeneous saturated porous media. The routine (1,1,1-TCA chain kinetic reactions) and subroutine (the relationship between hydraulic conductivity (K) and time (t)) were included in the model computer code. The simulation results suggested that the model C1 had the applicability for simulating contaminant transport and fate in bio-augmented flow field. By using the model C1 which was suitable for constant K condition, the performance of different types of Bio-PRBs was evaluated, and the regularity of contaminants chain kinetic reactions in different heterogeneous saturated porous media was obtained. The results demonstrated that Bio-PRBs in immobilized microorganism (IM) protocol were more superior to Bio-PRBs in free microorganism (FM) protocol. In addition, by using the model C2 (updated model C1) which was suitable for decreasing K condition, the different and optimized regularity of contaminants transport and transformation was obtained. The results showed that microbial growth which further decreased K was beneficial to preventing the transport of contaminants and accelerating the transformation of contaminants. However, the negative effects of biological clogging on hydraulic conductivity and relative hydraulic conductivity ratio in FM Bio-PRBs were significantly stronger than that in IM Bio-PRBs. Deploying IM Bio-PRBs for groundwater remediation would be much more efficient and meet the design criteria. The research work had guiding significance to engineering and provided consultation for designing and optimizing Bio-PRBs system. To make the design and optimization of Bio-PRBs system convenient, it was very essential to choose the suitable mathematical model (C1 or C2).
Funding Information
  • National Natural Science Foundation of China (41272261)
  • Science and Technology Commission of Shanghai Municipality (15DZ1205803)