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On-line Gas Diffusion Membrane Separation-Flow Injection Analysis with Spectrophotometric Detection for Automated Determination of Ammonia Nitrogen in Complex Industrial Wastewater

delete2026-04-22
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PRE
AI
J
Jun Hu
R
Rui Huang
P
Peng Li
Y
Yanli Hua
K
Kunde Lin
DOI:10.1039/D6AY00656Fdelete
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Abstract

Abstract

En 中文
Determination of ammonia nitrogen (NH 3 -N) in industrial wastewater is often challenged by complex matrix interference; and traditional laboratory analysis cannot provide timely feedback for dynamic process regulation. To address these issues; an automated online gas diffusion membrane separation-flow injection analysis system coupled with salicylate spectrophotometric detection was developed for the rapid determination of NH 3 -N in complex industrial wastewater. The method employs a hollow fiber membrane contactor to selectively separate volatile NH 3 from the complex matrix; effectively eliminating interferences. Under optimized conditions; the method exhibited a linear range of 1.0-50.0 mg L⁻ 1 (R² = 0.9997); with a limit of detection of 0.22 mg L⁻ 1 and limit of quantification of 0.72 mg L⁻ 1 . Precision was excellent; with relative standard deviations (RSDs) below 3.0%. The system showed strong anti-interference performance against salinity up to 35; common co-existing ions; and various organic nitrogen compounds. When applied to real industrial wastewater samples from an ammonia-stripping process; the proposed method provided good agreement with the reference salicylate method (HJ 536-2009) and higher spike recoveries (86.0%-96.7%) compared to the reference procedure. With a sample throughput of 14 samples per hour; the developed method offers a rapid; accurate; automated; and practical solution for high-frequency monitoring of NH 3 -N in complex industrial effluents; supporting improved process control and regulatory compliance.
Keywords:
Ammonia nitrogen
Gas diffusion membrane separation
Flow injection analysis
Spectrophotometric detection
Industrial wastewater

Journal

A
anal. methods
IF:
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382
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