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Efficiency of microbially assisted phytoremediation of heavy-metal contaminated soils

机译:重金属污染土壤微生物辅助植物修复的效率

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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 contaminated field sites.
机译:植物修复是使用植物及其相关的微生物来污染的土壤和水的生物修复。重金属(HM) - 酰胺土壤的植物修复基于根际土壤和根部(植物植物(植物植物)的金属的固定,并在制动,摄取和将金属转移到地上植物器官(植物申请)中。在本综述中,我们的目标是(i)讨论植物相关微生物(细菌和真菌)的基本面,潜力和局限性,以提高HM污染的土壤的植物毒性和植物萃取效率和(ii)描述有前途的发展和未来扩大他们使用的挑战。通过生长促进微生物的植物的受控接种可以显着提高其根部生长,生物质生产和抗汞污染土壤中的应力耐受性。植物修复的严重弱点通常是衡量成功完成时间的高且难以衡量的时间。生物浓缩因子(BCFS)和易位因子(TFS)是植物化效率的最重要措施之一。然而,缺乏BCFS和TFS的BCFS和TFS,缺乏具有定义相关的微生物的各种植物组合。此外,模型系统的联合评估将允许改善植物修复系统中微生物接种的成本效益计算。为此目的,由于节省时间和成本以及环境条件的控制,因此认为在体外模型系统的使用是优选的现场实验。然而,体外数据对现场条件的可转移性是有限的。目前,关注人工神经网络的使用,主要是避免在土壤输入(例如土壤修正,pH,碳,氮气和氢气含量,导电性和溶解的有机碳)和设计输出之间配制任何复杂关系(例如,BCF和TFS)预先和由于所获得的模型的高精度。相关微生物的受控使用以提高HM的植物化效率,主要使用甘蓝和Salix SPP的组合。污染的土壤中的根瘤菌是一个有前途的可能性。对其使用的扩展至关重要的未来挑战将是开发明确定义的成本和时效工具,以便可靠地预测其对受污染的现场网站的有效性。

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