## 4 Results and Discussion
### Pollutant Distribution  
In accordance with the site remediation strategy, the next step in the remediation process involves the injection and extraction treatment by opening all wells. Three types of pollutants are considered at the interface of dilute substances, with the initial pollutant distribution data and diffusion and adsorption parameters incorporated into the overall model. The simulation spans a duration of 55 days. After 55 days of remediation, the total amount of VOC decreased by 16.6%, reducing from 20.768 mol to 17.316 mol. The total amount of SVOC decreased by 23%, dropping from 2.9869 mol to 2.3 mol. Additionally, the total amount of EPH decreased by 42.5%, decreasing from 5.1552 mol to 2.9658 mol. The changes in pollutant concentrations from day zero to day 55 are presented in Figure 3.  
From Figure 3, it is evident that different types of pollutants exhibit distinct spatial distributions at day zero. Volatile and SVOC are primarily distributed to the west of the remediation area, which is attributed to the previous production activities in this region, resulting in the release of volatile chemicals. In contrast, EPH exhibit a relatively even distribution, present in both the central and northern parts of the factory area due to leakage from the factory's raw materials. Furthermore, Figure 3 illustrates that during the initial injection and extraction phases, pollutants tend to distribute more uniformly. This is because the external flow field disrupts the original equilibrium of pollutants, causing them to diffuse from areas of high concentrations to areas of lower concentrations. With increasing treatment times, the pollutants are removed from the extraction wells, desorb from the soil under the influence of the external flow and concentration fields, dissolve into groundwater, and are transported away by water flow. However, in the later stages of the extraction process, pollutants tend to approach the boundary region due to the difficulty of the flow field reaching the boundary. Pollutants that desorb in the soil near the boundary are reabsorbed. While \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Pollutant** & **Diffusion** & **Adsorption** & \\
**Type** & **Coefficient/m\({}^{2}\).s\({}^{-1}\)** & **Constant/mol kg\({}^{-1}\)** & **Adsorption Index** \\ \hline VOC & \(2\times 10^{-5}\) & \(3.63\times 10^{-3}\) & 1.09 \\ SVOC & \(1.3\times 10^{-4}\) & \(3.63\times 10^{-3}\) & 1.09 \\ EPH & \(2.3\times 10^{-3}\) & \(3.63\times 10^{-3}\) & 1.09 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Optimized parameter values. pollutant removal is more effective around the injection wells, it is not complete due to soil adsorption. To enhance removal, higher injection pressure or the use of surfactants can be considered. In this simulation, non-aqueous phase pollutants are not considered; all pollutants in the model are either dissolved in water or adsorbed onto soil. The addition of surfactants can reduce soil adsorption, leading to better remediation results. For this numerical simulation, the effect of adding surfactants is achieved by altering the Freundlich adsorption constant. The remediation results after 55 days for different Freundlich adsorption constants are presented in Figure 4.  
Figure 3: Changes in pollutant concentrations. From Figure 4, we gain a deeper understanding of the intricate relationship between the Freundlich adsorption constant and soil remediation efficiency. This relationship does not adhere to the simplistic principle of \"the smaller, the better\" but rather reveals a more nuanced dynamic equilibrium. The magnitude of the Freundlich adsorption constant directly influences the adsorption capacity of pollutants in the soil, where a smaller constant implies a stronger adsorption capacity under given conditions.