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authors |
Henriques, B; Teixeira, A; Figueira, P; Reis, AT; Almeida, J; Vale, C; Pereira, E |
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nationality |
International |
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journal |
SCIENCE OF THE TOTAL ENVIRONMENT |
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author keywords |
Macroalgae; Multi-contaminant; Removal; Wastewater; Cellular partition; Kinetic modelling |
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keywords |
SEQUENTIAL ELUTION TECHNIQUE; INDUSTRIAL WASTE-WATER; HEAVY-METAL IONS; FUCUS-VESICULOSUS; MARINE MACROALGA; AQUEOUS-SOLUTION; SALINE WATERS; BIOSORPTION; PB; CD |
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abstract |
This work shows the capabilities of living seaweed, Ulva lactuca, to remove As, Cd, Pb, Cu, Cr, Hg, Mn and Ni from contaminated waters. Experiments were performed with three algal doses (1.5, 3.0 and 6.0 g L-1, FW), two ionic strengths (salinity 15 and 35), and trace element concentrations corresponding to the maximum allowed values in wastewaters. The highest removals were obtained with the algal dose of 6 g L-1, with efficiencies varying between 48% for As and 98% for Hg, after 24 to 72 h. Salinity showed no effect on the removal efficiency. Overall, Elovich model was the best in describing the kinetics of the process, except for Hg, where pseudo-second-order model performed better. The use of extractions with EDTA (0.001, 0.01 to 0.1 mol L-1) has clarified that most of the Hg (approximate to 98%) and Cr (approximate to 80%) crossed the macroalgae walls, while Ni, Cd and As were retained at the surface (between 60 and 80%). These results support the hypothesis that macroalgae-based technologies may be a viable, cost-effective, and greener option to reduce the rejection of priority hazardous substances in contaminated waters. (C) 2018 Elsevier B.V. All rights reserved. |
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publisher |
ELSEVIER SCIENCE BV |
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issn |
0048-9697 |
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year published |
2019 |
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volume |
652 |
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beginning page |
880 |
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ending page |
888 |
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digital object identifier (doi) |
10.1016/j.scitotenv.2018.10.282 |
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web of science category |
Environmental Sciences |
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subject category |
Environmental Sciences & Ecology |
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unique article identifier |
WOS:000454418500081
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ciceco authors
impact metrics
journal analysis (jcr 2017):
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journal impact factor |
4.610 |
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5 year journal impact factor |
4.984 |
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category normalized journal impact factor percentile |
89.050 |
dimensions (citation analysis):
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altmetrics (social interaction):
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