Combining phytoremediation with bioenergy production: developing a multi‑criteria decision matrix for plant species selection

Amabogha, Obed Nadari, Garelick, Hemda ORCID: https://orcid.org/0000-0003-4568-2300, Jones, Huw ORCID: https://orcid.org/0000-0003-0024-864X and Purchase, Diane ORCID: https://orcid.org/0000-0001-8071-4385 (2023) Combining phytoremediation with bioenergy production: developing a multi‑criteria decision matrix for plant species selection. Environmental Science and Pollution Research . ISSN 0944-1344 [Article] (Published online first) (doi:10.1007/s11356-022-24944-z)

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Abstract

The use of plants to extract metal contaminants from soils has been proposed as a cost-effective means of remediation, and
utilizing energy crops for this phytoextraction process is a
useful way of attaining added value from the process. To simultaneously attain both these objectives successfully, selection of an appropriate plant species is crucial to satisfy a number of important criteria including translocation index, metal
and drought tolerance, fast growth rate, high lignocellulosic content, good biomass production, adequate calorific value, second generation attribute, and a good rooting system. In this study, we proposed a multi-criteria decision analysis (MCDA) to aid decision-making on plant species based on information generated from a systematic review survey. Eight species Helianthus annuus (sunflower), Brassica juncea (Indian mustard), Glycine max (soybean), Salix spp. (willow), Populus spp. (poplar), Panicum virgatum (switchgrass), Typha latifolia (cattails), and Miscanthus sinensis (silvergrass) were examined based on the amount of hits on a number of scientific search databases. The data was normalized by estimating their min–max values and their suitability. These criteria/indicators were weighted based on stipulated research objectives/priorities to form the basis of a final overall utility scoring. Using the MCDA, sunflower and silvergrass emerged as the top two candidates for both phytoremediation and bioenergy production. The multi-criteria matrix scores assist the process of making decisions because they compile plant species options quantitatively for all relevant criteria and key performance indicators (KPIs) and its weighing process helps incorporate stakeholder priorities to the selection process.

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