Department of Civil Engineering and Smart Cities, College of Engineering, Shantou University, Shantou, 515063, Guangdong, China.
Environ Sci Pollut Res Int. 2024 Aug;31(40):52905-52916. doi: 10.1007/s11356-024-34725-5. Epub 2024 Aug 21.
In this research paper, we introduce a novel and sustainable approach for forecasting the hydraulic conductivity of sand layers subjected to microbial-induced carbonate precipitation (MICP) to mitigate the diffusion of toxic pollutants. The proposed model uniquely integrates the impact of varying CaCO contents on the void ratio and estimates the average particle size of CaCO crystals through scanning electron microscopy (SEM) analysis. By incorporating these parameters into the K-C equation, a simplified predictive model is formulated for assessing the hydraulic conductivity of MICP-treated sand layers. The model's effectiveness is validated through comparison with experimental data and alternative models. The outcomes demonstrate a substantial reduction in hydraulic conductivity, with a decrease ranging between 93 and 97% in the initial assessment and a decrease between 67 and 92% in the follow-up assessment, both at 10% CaCO content. Notably, the hydraulic conductivity shows an initial sharp decrease followed by stabilization. These findings provide valuable insights into improving the prediction of hydraulic conductivity in MICP-treated sand layers, promoting a sustainable method for preventing pollution dispersion.
在本研究论文中，我们介绍了一种新颖且可持续的方法，用于预测微生物诱导碳酸钙沉淀 (MICP) 处理后的砂层的水力传导率，以减轻有毒污染物的扩散。所提出的模型独特地整合了 CaCO3 含量变化对空隙比的影响，并通过扫描电子显微镜 (SEM) 分析估计 CaCO3 晶体的平均粒径。通过将这些参数纳入 K-C 方程，我们制定了一个简化的预测模型，用于评估 MICP 处理砂层的水力传导率。通过与实验数据和替代模型进行比较，验证了该模型的有效性。结果表明，水力传导率显著降低，在初始评估中降低了 93%至 97%，在后续评估中降低了 67%至 92%，CaCO3 含量均为 10%。值得注意的是，水力传导率呈现出初始急剧下降随后稳定的趋势。这些发现为改善 MICP 处理砂层水力传导率的预测提供了有价值的见解，促进了防止污染扩散的可持续方法。
