Highly efficient lead extraction from aqueous solutions using inorganic polymer foams derived from biomass fly ash and metakaolin
authors Novais, RM; Carvalheiras, J; Seabra, MP; Pullar, RC; Labrincha, JA
nationality International
journal JOURNAL OF ENVIRONMENTAL MANAGEMENT
author keywords Alkali-activated material; Adsorption; Waste; Lead; Foam
keywords HEAVY-METAL ADSORPTION; WASTE-WATER; GEOPOLYMER; REMOVAL; IMMOBILIZATION; ADSORBENT; MICROSTRUCTURE; STRENGTH; SPHERES; GREEN
abstract This work reports a simple and safe, but powerful, route to depollute lead-containing aqueous solutions. Inorganic polymer foams (cm-size) were used as bulk-type adsorbents. The influence of the specimens' porosity and activator molarity on the foams' physical properties and on their lead extraction ability was studied. Then, the best performing samples were deeply evaluated as lead adsorbents by studying the impact of pH, lead concentration, contact time, ionic strength and solution volume. Lead sorption kinetics is strongly affected by the pollutant concentration, pH and the solution ionic strength. Under the most favourable conditions the foams showed an impressive removal capacity (105.9 mg/g at pH 5, 23 degrees C, C-0 = 800 ppm, deionised water), surpassing all other reported values on the use of bulk-type inorganic polymers. The foams' lead uptake is 2.3 times higher than the previous best performing bulk-type specimens (mm-size spheres), and sorption is 12.5-15 times faster. The foams can be easily regenerated using mild acidic conditions, and then reused as adsorbent, suggesting that the main adsorption mechanism is ion exchange.
publisher ACADEMIC PRESS LTD- ELSEVIER SCIENCE LTD
issn 0301-4797
isbn 1095-8630
year published 2020
volume 272
digital object identifier (doi) 10.1016/j.jenvman.2020.111049
web of science category Environmental Sciences
subject category Environmental Sciences & Ecology
unique article identifier WOS:000574828400004
  ciceco authors
  impact metrics
journal analysis (jcr 2019):
journal impact factor 5.647
5 year journal impact factor 5.708
category normalized journal impact factor percentile 87.736
dimensions (citation analysis):
altmetrics (social interaction):



 


Apoio

1suponsers_list_ciceco.jpg