Phytoremediation can be used as a sustainable technology for mine spoil remediation to remove heavy metals. This study investigated the concentration of 7 heavy metal contamination in soil and plant samples at an aban...Phytoremediation can be used as a sustainable technology for mine spoil remediation to remove heavy metals. This study investigated the concentration of 7 heavy metal contamination in soil and plant samples at an abandoned mine site. We found that, after vegetation remediation at the abandoned mine site, the reduction rates for 7 heavy metals were in the range of 4.2%-86%, where reduction rates over 50% were achieved for four heavy metals （Zn, Mn, Cd, Ni）. Transfer coefficients of the panicled goldenrain tree （Koelreuteria paniculata Laxm） and the common elaeocarpus （Elaeocarpus decipens） for Zn, Mn, Ni, and Co were more than 1. Enrichment coefficients of both trees for Mn were higher than 1. Our results suggest that the panicled goldenrain tree and the common elaeocarpus tree may act as accumulators in remediation. Moreover, the woody vegetation remediation in abandoned mining areas play an important role in improving scenery besides removing heavy metal from contaminated soil.展开更多
Fields that employ artificial neural networks(ANNs)have developed and expanded continuously in recent years with the ongoing development of computer technology and artificial intelligence.ANN has been adopted widely a...Fields that employ artificial neural networks(ANNs)have developed and expanded continuously in recent years with the ongoing development of computer technology and artificial intelligence.ANN has been adopted widely and put into practice by research-ers in light of increasing concerns over ecological issues such as global warming,frequent El Nio-Southern Oscillation(ENSO)events,and atmospheric circulation anomalies.Limitations exist and there is a potential risk for misuse in that ANN model pa-rameters require typically higher overall sensitivity,and the chosen network structure is generally more dependent upon individ-ual experience.ANNs,however,are relatively accurate when used for short-term predictions;despite global climate change re-search favoring the effects of interactions as the basis of study and the preference for long-term experimental research.ANNs remain a better choice than many traditional methods when dealing with nonlinear problems,and possesses great potential for the study of global climate change and ecological issues.ANNs can resolve problems that other methods cannot.This is especially true for situations in which measurements are difficult to conduct or when only incomplete data are available.It is anticipated that ANNs will be widely adopted and then further developed for global climate change and ecological research.展开更多
基金As a key project under the State Forestry Administration of China (2006-11, 2006-17, 2005-08)this project was funded by the National Natural Science Foundation of China (No. 30571487, 30771700)+1 种基金the Furong Scholar Program, the Urban Forest Ecological Key Laboratory of Hunan Province (No. 06FJ3083)the Platform Construction Project under the Ministry of Science and Technology of China
文摘Phytoremediation can be used as a sustainable technology for mine spoil remediation to remove heavy metals. This study investigated the concentration of 7 heavy metal contamination in soil and plant samples at an abandoned mine site. We found that, after vegetation remediation at the abandoned mine site, the reduction rates for 7 heavy metals were in the range of 4.2%-86%, where reduction rates over 50% were achieved for four heavy metals （Zn, Mn, Cd, Ni）. Transfer coefficients of the panicled goldenrain tree （Koelreuteria paniculata Laxm） and the common elaeocarpus （Elaeocarpus decipens） for Zn, Mn, Ni, and Co were more than 1. Enrichment coefficients of both trees for Mn were higher than 1. Our results suggest that the panicled goldenrain tree and the common elaeocarpus tree may act as accumulators in remediation. Moreover, the woody vegetation remediation in abandoned mining areas play an important role in improving scenery besides removing heavy metal from contaminated soil.
基金supported by the Introducing Advanced Technology Program(948Pro-gram)(2010-4-03)the New Century Excellent Talents Program from the Ministry of Education,China(NCET-06-0715)+1 种基金the Program for Science and Technology Innovative Research Team in Higher Educational Institutions of Hunan Provincethe Furong Scholar Program
文摘Fields that employ artificial neural networks(ANNs)have developed and expanded continuously in recent years with the ongoing development of computer technology and artificial intelligence.ANN has been adopted widely and put into practice by research-ers in light of increasing concerns over ecological issues such as global warming,frequent El Nio-Southern Oscillation(ENSO)events,and atmospheric circulation anomalies.Limitations exist and there is a potential risk for misuse in that ANN model pa-rameters require typically higher overall sensitivity,and the chosen network structure is generally more dependent upon individ-ual experience.ANNs,however,are relatively accurate when used for short-term predictions;despite global climate change re-search favoring the effects of interactions as the basis of study and the preference for long-term experimental research.ANNs remain a better choice than many traditional methods when dealing with nonlinear problems,and possesses great potential for the study of global climate change and ecological issues.ANNs can resolve problems that other methods cannot.This is especially true for situations in which measurements are difficult to conduct or when only incomplete data are available.It is anticipated that ANNs will be widely adopted and then further developed for global climate change and ecological research.
