Xu Da-Mao, Fu Rong-Bing, Wang Jun-Xian, An Bai-Hong
State Key Laboratory of Pollution Control and Resource Reuse, College of Environmental Science and Engineering, Tongji University, Shanghai 200092, PR China; Centre for Environmental Risk Management and Remediation of Soil and Groundwater, Tongji University, Shanghai 200092, PR China; Shanghai Institute of Pollution Control and Ecological Security, Shanghai 200092, PR China.
Centre for Environmental Risk Management and Remediation of Soil and Groundwater, Tongji University, Shanghai 200092, PR China; Viterbi School of Engineering, University of Southern California, Los Angeles, CA 90089, United States.
J Hazard Mater. 2022 Feb 15;424(Pt A):127127. doi: 10.1016/j.jhazmat.2021.127127. Epub 2021 Sep 11.
This study comprehensively investigated the potential roles of soil mineralogy identified by the automated mineral liberation analysers (MLA) in the prediction of geochemical behavior of toxic metals in the smelter polluted soils. The results from modal mineralogy revealed that the non-reactive silicate phases such as quartz (42.05%) and biotite (40.43%) were the major mineralogical phases. The element deportment showed that fayalite, lead oxide, apatite, galena and wollastonite were identified as the dominant As, Cd, Pb and Zn bearing minerals. Furthermore, MLA analysis also confirmed that Pb was most concentrated in the smaller particles of lead oxide, which significantly enhanced Pb release in reaction with the chemical extractant during chemical kinetic tests. The results from pH-dependent leaching tests indicated that the leaching concentrations of As, Pb and Zn increased at low and high pH values, but were lowest at the neutral pH range. In addition, the results from the kinetic study demonstrated that the second order model provided the best description for the release patterns of the main metal contaminants in the bioavailability and bioaccessibility tests. The integrated geochemical analysis demonstrated that among these studied elements, As showed a typical geochemical pattern, which was predominantly controlled by 90.09% of fayalite. The above study results would have significant implications for soil remediation and risk management of smelter contaminated sites.
本研究全面调查了自动矿物解离分析仪(MLA)识别出的土壤矿物学在预测冶炼厂污染土壤中有毒金属地球化学行为方面的潜在作用。模态矿物学结果显示,石英(42.05%)和黑云母(40.43%)等非反应性硅酸盐相是主要的矿物相。元素赋存情况表明,铁橄榄石、氧化铅、磷灰石、方铅矿和硅灰石被确定为主要的含砷、镉、铅和锌矿物。此外,MLA分析还证实,铅在氧化铅的较小颗粒中最为富集,这在化学动力学试验中与化学萃取剂反应时显著增强了铅的释放。pH依赖浸出试验结果表明,砷、铅和锌的浸出浓度在低pH值和高pH值时增加,但在中性pH范围内最低。此外,动力学研究结果表明,二级模型对生物有效性和生物可及性试验中主要金属污染物的释放模式提供了最佳描述。综合地球化学分析表明,在所研究的这些元素中,砷呈现出典型的地球化学模式,主要受90.09%的铁橄榄石控制。上述研究结果对冶炼厂污染场地的土壤修复和风险管理具有重要意义。