Literature DB >> 31280029

Cellulose-hydroxyapatite carbon electrode composite for trace plumbum ions detection in aqueous and palm oil mill effluent: Interference, optimization and validation studies.

Huma Ajab1, Aamir Amanat Ali Khan2, Muhammad Shahid Nazir3, Asim Yaqub4, Mohd Azmuddin Abdullah5.   

Abstract

Environmental monitoring is important to determine the extent of eco-system pollution and degradation so that effective remedial strategies can be formulated. In this study, an environmentally friendly and cost-effective sensor made up of novel carbon electrode modified with cellulose and hydroxyapatite was developed for the detection of trace lead ions in aqueous system and palm oil mill effluent. Zinc, cadmium, and copper with lead were simultaneously detected using this method. The electrode exhibited high tolerance towards twelve common metal ions and three model surface active substances - sodium dodecyl sulfate, Triton X-100, and cetyltrimethylammonium bromide. Under optimum conditions, the sensor detected lead ions in palm oil mill effluent in the concentration range of 10-50 μg/L with 0.11 ± 0.37 μg/L limit of detection and 0.37 ± 0.37 μg/L limit of quantification. The validation using tap water, blood serum and palm oil mill effluent samples and compared with Atomic Absorption Spectroscopy, suggested excellent sensitivity of the sensor to detect lead ions in simple and complex matrices. The cellulose produced based on "green" techniques from agro-lignocellulosic wastes, in combination with hydroxyapatite, were proven effective as components in the carbon electrode composite. It has great potential in both clinical and environmental use.
Copyright © 2019 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Cellulose; Chemical sensor; Environmental monitoring; Heavy metal ion; Hydroxyapatite

Year:  2019        PMID: 31280029     DOI: 10.1016/j.envres.2019.108563

Source DB:  PubMed          Journal:  Environ Res        ISSN: 0013-9351            Impact factor:   6.498


  1 in total

1.  Coupling Square Wave Anodic Stripping Voltammetry with Support Vector Regression to Detect the Concentration of Lead in Soil under the Interference of Copper Accurately.

Authors:  Ning Liu; Guo Zhao; Gang Liu
Journal:  Sensors (Basel)       Date:  2020-11-27       Impact factor: 3.576

  1 in total

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