4.7 Article

A rapid and economical method for the quantification of hydrogen peroxide (H2O2) using a modified HPLC apparatus

期刊

SCIENCE OF THE TOTAL ENVIRONMENT
卷 654, 期 -, 页码 107-117

出版社

ELSEVIER
DOI: 10.1016/j.scitotenv.2018.10.372

关键词

H2O2; Quantification; AOPs; ISCO; HPLC

资金

  1. LNCSR of the American University of Beirut [103250]
  2. K Shair CRSL Fund of the American University of Beirut [103191]
  3. University Research Board of the American University of Beirut [103186]
  4. USAID-Lebanon through the National Academy of Sciences under PEER project 5-18 [103262]

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H2O2 is one of the most commonly used oxidants for the degradation of recalcitrant organic contaminants in advanced oxidation processes (AOPs). However, most research aiming to optimize AOPs is missing the monitoring of the remaining H2O2, an important parameter to assess the efficiency of the process. in this work, a novel method for [H2O2] quantification was developed using simple modifications of an HPLC-DAD setup that is available in most analytical chemistry laboratories. The modifications include the use of acidified potassium iodide solution as mobile phase and replacing the reverse phase column with a series of capillary columns. This instrument configuration allowed also the quantification of organic contaminants using the same H2O2 containing sample. The method's LOD and LOQ were calculated to be as low as 8.29 x 10(-4) mM and 2.76 x 10(-3) mM, respectively with an LDR range of 0.01-150 mM. The cost per analysis ranged between 0.8 and 1.8 USD cents depending on the concentration tested. This analytical method was validated by a statistical comparison to a well-known titrimetric method that is commonly used for H2O2 quantification. It was also tested using standards prepared in natural matrices such as spring and seawater, and in media containing high concentration of several spectator species such as chlorides, bicarbonates, humic acids, fumaric acids and micro pollutants. The method showed excellent robustness by maintaining high regression coefficient and excellent sensitivity in all calibration curves regardless of the matrix content. (C) 2018 Elsevier B.V. All rights reserved.

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