Jianluan Chen,Xiaoyan Bai,Yong Yuan,Yaping Zhang,Jian Sun
Printing and dyeing sludge (PADS) is considered hazardous waste and difficult to dispose of. Traditional sludge disposal technologies lead to land occupation and dioxin generation, as well as the lack of resource utilization of sludge. In this study, PADS biochar was prepared by pyrolysis technology and used as a peroxymonosulfate (PMS) activator to remove organic pollutants in water for the first time, and the safety of its use was evaluated. The results showed that PADS biochar prepared under optimized conditions of 800 °C for 1.5 h (BC-800-1.5) could efficiently activate PMS and achieve 99% removal of bisphenol A (BPA) within 20 min which was more efficient than BC-800-1.5 adsorption alone (12%) and oxidation by single PMS (4%). Radical trapping experiments suggested that 1 O 2 -dominated non-radical activation pathway was responsible for BPA degradation. By further characterization, C O, graphite nitrogen and pyridine nitrogen on the PDAS surface were identified as active sites for PMS activation. The results of safety evaluation experiment showed that the content of polycyclic aromatic hydrocarbon in BC-800-1.5 and heavy metals leached from BC-800-1.5 were well within the corresponding standards. This research had developed a new technological approach to simultaneously realize the resource utilization and eliminate the environmental hazards of PADS sludge.
Jie Cheng,Yuxin Qiu,Jiahui Chen,Yuqi Gu,Jingwen Wang,Guzhong Chen,Zhiwen Qi,Zhen Song
The inherent merits of natural deep eutectic solvents (NADESs) have endowed them as a class of promising solvents in many applications. In this study, amino acid-based DESs are applied as absorbent for CO 2 capture. A systematic method combining solid–liquid equilibria (SLE) prediction, EHS-impacts (environmental, health, and safety) evaluation of the second components, and experimental validation is employed to rationally identify promising CO 2 absorbents. The melting point and fusion enthalpy of pure amino acid components are predicted by a recently proposed machine learning model, while COSMO-RS is used to predict the SLE of all possible combinations. Five key EHS-related properties of the second components are evaluated via the VEGA platform. From above, eight promising binary systems based on L-lysine and L-proline are screened from the initial pool of 2,500 combinations. The SLE, density, and viscosity are experimentally determined and the CO 2 absorption experiments are finally performed, identifying L-proline: nonanoic acid (1:4) as the most promising eutectic absorbent.
危险品化学品经营许可证（带存储）