Efficiency of microbially assisted phytoremediation of heavy-metal contaminated soils
Phytoremediation is the bioremediation of contaminated soils and waters by using plants and their associated microorganisms. Phytoremediation of heavy metal (HM)-contaminated soils is based on immobilization of metals in rhizosphere soil and roots (phytostabilization) and on mobilization, uptake, an...
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| Published in: | Environmental reviews 2018-09, Vol.26 (3), p.316-332 |
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| Main Authors: | , , , , |
| Format: | Article |
| Language: | eng |
| Subjects: | |
| Online Access: | Get full text |
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| Summary: | Phytoremediation is the bioremediation of contaminated soils and waters by using plants and their associated microorganisms. Phytoremediation of heavy metal (HM)-contaminated soils is based on immobilization of metals in rhizosphere soil and roots (phytostabilization) and on mobilization, uptake, and transfer of metals into the aboveground plant organs (phytoextraction). In this review, we aimed to (i) discuss the fundamentals, potential, and limitations of plant-associated microorganisms (bacteria and fungi) to increase the efficiency of phytostabilization and phytoextraction of HM-contaminated soils and (ii) describe promising developments and future challenges to expanding their use. Controlled inoculations of plants with growth-promoting microorganisms can significantly increase their root growth, biomass production, and stress tolerance in HM-contaminated soils. A serious weakness of phytoremediation in general is the usually high and difficult to measure expenditure of time for successful completion. The bioconcentration factors (BCFs) and the translocation factors (TFs) are among the most important measures of the efficiency of phytoremediation. However, an overview of BCFs and TFs for a variety of combinations of plants with defined associated microorganisms is lacking. Moreover, the joint evaluation of model systems would allow an improved cost–benefit calculation of microbial inoculations in phytoremediation systems. For this purpose, the use of in vitro model systems is considered to be preferable to field experiments due to the savings in time and costs and the control of environmental conditions. However, the transferability of in vitro data to field conditions is limited. Currently, attention is focused on the use of artificial neural networks, mainly to avoid formulating any complex relationships between soil inputs (e.g., soil amendments, pH, carbon, nitrogen and hydrogen contents, electrical conductivity, and dissolved organic carbon) and design outputs (e.g., BCFs and TFs) beforehand and because of the high accuracy of the obtained models. The controlled use of associated microorganisms to increase the efficiency of phytoremediation of HM, mainly using combinations of Brassica and Salix spp. and rhizobacteria at contaminated soils, is a promising possibility. A crucial future challenge for the expansion of their use will be to develop well-defined cost- and time-efficient tools for a credible prediction of their effectiveness on contamina |
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| ISSN: | 1181-8700 1208-6053 |