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Anning Refinery, a large-scale joint venture in southern China, possesses significant potential in regard to polluting local groundwater environments due to its extensive petroleum raw materials. This study aims to mitigate the substantial risks associated with oil spills and prevent consequential groundwater pollution by developing a robust groundwater flow model using the MODFLOW module in GMS software that aligns closely with natural and pumping test conditions. Furthermore, by integrating the MT3DMS model, a groundwater solute transport model is constructed and calibrated using sodium chloride tracer dispersion data. Notably, the wax hydrocracking unit and aviation coal finished product tank area are identified as key pollution sources warranting attention. By considering local constraints such as karst collapse, ground subsidence, and single-well water output capacity, the study introduces a tailored groundwater pollution management model. The research simulates various scenarios of petroleum pollutant migration in groundwater and proposes multi-objective emergency response optimization plans. In Scenario 1, simulations show that petroleum pollutants migrate within the unconfined aquifer and enter the karst aquifer as low-concentration plumes over an extended period. Detection of these plumes in karst water monitoring wells indicates upstream unconfined aquifer contamination at higher concentrations, necessitating immediate activation of the nearest monitoring or emergency wells in both layers. Conversely, in Scenario 2, pollutants reside briefly in the unconfined aquifer before entering the karst aquifer at relatively higher concentrations. Here, low-efficiency pollutant discharge through unconfined aquifer monitoring wells prompts the activation of nearby karst aquifer monitoring or emergency wells for effective pollution control. This model underscores the necessity for proactive monitoring and validates the efficacy of coupled numerical modeling in understanding pollutant behavior, offering valuable insights into pollution control scenario assessments. In summary, the study emphasizes the importance of targeted monitoring and emergency protocols, demonstrating the benefits of integrated modeling approaches in industrial areas prone to pollution risks, and provides critical theoretical and practical guidance for groundwater protection and pollution management, offering transferable insights for similar industrial settings worldwide.

In this paper, we evaluated the potential of two synthesized bio-based polyurethane foams, PU1 and PU2, for the removal of diesel and gasoline from water mixtures. We started the investigation with the experiment in batch. The total sorption capacity S (g/g) for the diesel/water system was slightly higher with respect to gasoline/water, with a value of 62 g/g for PU1 and 65 g/g for PU2. We found that the sorption follows a pseudo second-order kinetic model for both the materials. The experimental data showed that the best isotherm models were obtained with Langmuir and Redlich–Peterson models. In addition, to provide an idea of the process scalability for future industrial applications, we tested the sorption capacity of the foams using a continuous-flow of the same oil/water mixtures and we obtained performances even better with respect to the batch test. The regeneration can be performed up to 50 times by centrifuge, without losing efficacy.