Restoration of red mud deposits by naturally growing vegetation

ABSTRACT

Disposal of red mud (RM) poses serious environmental problems such as wind erosion, air and water pollution. To overcome these problems, effective restoration of the disposal land through naturally growing vegetation is a sustainable and economical approach. The present study involved estimation of frequency (F), density (D), abundance (Ab), and important value index (IVI) of natural flora on abandoned RM sites in order to assess their metal toxicity tolerance capacity. Based on visual observations and highest IVI, S. Asper and S. punicea were identified as effective ecological tools for the restoration of barren RM sites. From the study, remarkable differences were observed between non-rhizospheric and rhizospheric RM of both species. These rhizospheric RM analyses confirm the ability of S. asper and S. punicea for enhancing the biological activities of abandoned RM. Translocation factor (TF) of iron was maximum (2.58) in S. asper, and bioconcentration factor (BCF) was found maximum (1.25) in S. punicea, but both TF (2.58) and BCF (1.35) were high in S. asper. Therefore, this plant could be reported as an iron hyperaccumulator plant. These results suggest that these plant species can be exploited for effective restoration of RM deposited land without any inputs or maintenance.

KEYWORDS:

• naturally growing vegetation
• heavy metals
• red mud
• restoration

Acknowledgments

The authors are grateful to the director, NBRI, for keen interest and continuous encouragement to conduct the experiments. Authors express their special thanks to Hindalco Industries Pvt. Limited, Renukoot, for permitting this biodiversity study on their dumping site. They also express their special thanks to Mr Arun Kushwaha for his help in identification of plants. Tripti Mishra is grateful to the Department of Science & Technology for the DST-INSPIRE- Senior Research Fellowship. The authors are thankful to the editor and four anonymous reviewers for their very helpful suggestions that improved the manuscript.

Funding

This work was financially supported by CSIR, GOI network project “INDEPTH” (BSC 0111).