Coupling bioaccumulation and phytotoxicity to predict copper removal by switchgrass grown hydroponically
A major challenge in phytoextraction is to increase plants' removal rates of metals from contaminated soils. In this study, we developed a phytoextraction model, by coupling a saturable Michaelis-Menten type accumulation model and an energy-based toxicity model, to predict copper (Cu) removal b...
Veröffentlicht in: | Ecotoxicology (London, England). - 1992. - 20(2011), 4 vom: 21. Juni, Seite 827-35 |
---|---|
1. Verfasser: | |
Weitere Verfasser: | , |
Format: | Online-Aufsatz |
Sprache: | English |
Veröffentlicht: |
2011
|
Zugriff auf das übergeordnete Werk: | Ecotoxicology (London, England) |
Schlagworte: | Journal Article Research Support, Non-U.S. Gov't Water Pollutants, Chemical Copper 789U1901C5 |
Zusammenfassung: | A major challenge in phytoextraction is to increase plants' removal rates of metals from contaminated soils. In this study, we developed a phytoextraction model, by coupling a saturable Michaelis-Menten type accumulation model and an energy-based toxicity model, to predict copper (Cu) removal by switchgrass (Panicum virgatum L.) grown hydroponically under various exposure concentrations. Results of the present study indicated that the phytotoxicity of Cu to switchgrass is relatively low, whereas a certain accumulation capacity exists in the plant for Cu. In addition, the simulation results suggested that, under a lower dissolved concentration, Cu removal is increased more efficiently as the exposure duration increases. Although it is difficult to extrapolate the results from greenhouse-based hydroponic experiments to field conditions, we believe that the current methodology can offer a first approximation in predicting the phytoextraction duration needed for plant species to remove a specific metal from contaminated sites, which is crucial in evaluating the economic costs for remediation purposes |
---|---|
Beschreibung: | Date Completed 27.07.2011 Date Revised 20.10.2021 published: Print-Electronic Citation Status MEDLINE |
ISSN: | 1573-3017 |
DOI: | 10.1007/s10646-011-0635-z |