The contamination of heavy metal(loid)s at mining&metallurgical sites has been a major environmental challenge worldwide[1].Typically,large amounts of metal(loid)s-bearing wastes are generated at these sites,such ...The contamination of heavy metal(loid)s at mining&metallurgical sites has been a major environmental challenge worldwide[1].Typically,large amounts of metal(loid)s-bearing wastes are generated at these sites,such as smelting slag,combustion residues,mine tailings,wastewater,and exhaust gas[2].Due to their high mobility in the environment,the released heavy metal(loid)s can easily enter the soil and water environment,posing long-term and widespread threats to ecological and human health[3].展开更多
A novel integrated approach to remove the free alkalis and stabilize solid-phase alkalinity by controlling the release of Ca from desulfurization gypsum was developed.The combination of recycled FeCl_(3)solution and E...A novel integrated approach to remove the free alkalis and stabilize solid-phase alkalinity by controlling the release of Ca from desulfurization gypsum was developed.The combination of recycled FeCl_(3)solution and EDTA activated desulfurization gypsum lowered the bauxite residue pH to 7.20.Moreover,it also improved the residual Ca state,with its contribution to the total exchangeable cations increased(68%-92%).Notably,the slow release of exchangeable Ca introduced through modified desulfurization gypsum induced a phase transition of the alkaline minerals.This treatment stabilized the dealkalization effect of bauxite residue via reducing its overall acid neutralization capacity in abating pH rebound.Hence,this approach can provide guidance for effectively utilizing desulfurization gypsum to achieve stable regulation of alkalinity in bauxite residue.展开更多
A general prediction model for seven heavy metals was established using the heavy metal contents of 207soil samples measured by a portable X-ray fluorescence spectrometer(XRF)and six environmental factors as model cor...A general prediction model for seven heavy metals was established using the heavy metal contents of 207soil samples measured by a portable X-ray fluorescence spectrometer(XRF)and six environmental factors as model correction coefficients.The eXtreme Gradient Boosting(XGBoost)model was used to fit the relationship between the content of heavy metals and environment characteristics to evaluate the soil ecological risk of the smelting site.The results demonstrated that the generalized prediction model developed for Pb,Cd,and As was highly accurate with fitted coefficients(R~2)values of 0.911,0.950,and 0.835,respectively.Topsoil presented the highest ecological risk,and there existed high potential ecological risk at some positions with different depths due to high mobility of Cd.Generally,the application of machine learning significantly increased the accuracy of pXRF measurements,and identified key environmental factors.The adapted potential ecological risk assessment emphasized the need to focus on Pb,Cd,and As in future site remediation efforts.展开更多
基金the financial support by the National Key Research and Development Program of China and the Natural Science Foundation of Hunan Province (2019YFC18 03600, 2019YFC1803500, 2019YFC1805200, 2020YFC1807700, 2020YFC1808300, 2021YFC29 02600, 2022YFC2904400, 2023YFC3707700, 2024JJ1012)
文摘The contamination of heavy metal(loid)s at mining&metallurgical sites has been a major environmental challenge worldwide[1].Typically,large amounts of metal(loid)s-bearing wastes are generated at these sites,such as smelting slag,combustion residues,mine tailings,wastewater,and exhaust gas[2].Due to their high mobility in the environment,the released heavy metal(loid)s can easily enter the soil and water environment,posing long-term and widespread threats to ecological and human health[3].
基金Project(2019YFC1803601)supported by the National Key Research and Development Program of ChinaProject(2022)supported by the Complementary Fund from the Guizhou Provincial Department of Science and Technology,China。
基金Project(2019YFC1803601)supported by the National Key Research and Development Program of ChinaProject(42177392)supported by the National Natural Science Foundation of China+1 种基金Project(RG 45/2022-2023R)supported by the Research and Development Office,the Education University of Hong Kong,ChinaProject(IRS-42023)supported by the Dean's Research Fund of Education University of Hong Kong,China。
基金Project(42030711)supported by the Key Project of National Natural Science Foundation of ChinaProject(42177391)supported by the National Natural Science Foundation of China。
基金Project(2019YFC1803603)supported by the National Key R&D Program of ChinaProject(2024JJ4061)supported by the Natural Science Foundation of Hunan Province,ChinaProject(2023ZZTS0517)supported by the Fundamental Research Funds for the Central Universities of Central South University,China。
基金supported by the National Natural Science Foundation of China(No.42307521)the China Postdoctoral Science Foundation(No.2023M742934)。
文摘A novel integrated approach to remove the free alkalis and stabilize solid-phase alkalinity by controlling the release of Ca from desulfurization gypsum was developed.The combination of recycled FeCl_(3)solution and EDTA activated desulfurization gypsum lowered the bauxite residue pH to 7.20.Moreover,it also improved the residual Ca state,with its contribution to the total exchangeable cations increased(68%-92%).Notably,the slow release of exchangeable Ca introduced through modified desulfurization gypsum induced a phase transition of the alkaline minerals.This treatment stabilized the dealkalization effect of bauxite residue via reducing its overall acid neutralization capacity in abating pH rebound.Hence,this approach can provide guidance for effectively utilizing desulfurization gypsum to achieve stable regulation of alkalinity in bauxite residue.
基金financially supported from the National Key Research and Development Program of China(No.2019YFC1803601)the Fundamental Research Funds for the Central Universities of Central South University,China(No.2023ZZTS0801)+1 种基金the Postgraduate Innovative Project of Central South University,China(No.2023XQLH068)the Postgraduate Scientific Research Innovation Project of Hunan Province,China(No.QL20230054)。
文摘A general prediction model for seven heavy metals was established using the heavy metal contents of 207soil samples measured by a portable X-ray fluorescence spectrometer(XRF)and six environmental factors as model correction coefficients.The eXtreme Gradient Boosting(XGBoost)model was used to fit the relationship between the content of heavy metals and environment characteristics to evaluate the soil ecological risk of the smelting site.The results demonstrated that the generalized prediction model developed for Pb,Cd,and As was highly accurate with fitted coefficients(R~2)values of 0.911,0.950,and 0.835,respectively.Topsoil presented the highest ecological risk,and there existed high potential ecological risk at some positions with different depths due to high mobility of Cd.Generally,the application of machine learning significantly increased the accuracy of pXRF measurements,and identified key environmental factors.The adapted potential ecological risk assessment emphasized the need to focus on Pb,Cd,and As in future site remediation efforts.
文摘针对目前国内锰超富集植物商陆属(Phytolacca)植物名称混乱的状态,在重新审查锰超富集植物——商陆(Phytolacca acinosa Roxb.)的野外标本和温室培养植物的基础上,比对中国科学院昆明植物所标本馆的腊叶标本,并查阅相关文献资料,以期正确认定锰超富集累植物的学名。结果表明,湘潭锰矿尾矿废弃地原生的锰超富集植物实为垂序商陆(Phytolacca americana L.),国内外相关研究论文中出现的商陆和美洲商陆实为垂序商陆的同物异名。这一植物名称的认定,将对避免锰超富集植物研究重复进行、保证相关研究正常有序开展具有重要意义。
