The influence of hydroxylamine on Fe coagulation when treating NOM and TC from real-world waters
File(s)
Accepted version
Author(s)
Song, Qingyun
Yang, Bingqian
Zhang, Kai
Graham, Nigel
Yu, Wenzheng
Type
Journal Article
Abstract
Coagulation occurs everywhere in natural aquatic environment and is widely used in water treatment. However, the influence of reducing substances on coagulation has long been overlooked. And one limitation of coagulation is its low efficiency in removing organics of low molecular weight (MW). In this study, we investigated the influence of hydroxylamine (HA), a representative reducing substance, on iron (Fe) coagulation when treating natural organic matter (NOM) and tetracycline (TC); the latter selected as a representative low MW micro-pollutant. It was found that HA enhanced the removal of organics from the effluent water (the Olympic Park Lake water, OP) and surface water (the Jingmi River water, JM) employed in the experiments. Also, the simultaneous enhanced removal of NOM and TC was achieved in the coagulation process. In addition, HA not only enhanced the removal of TC of low MW, but also improved the NOM removal of low MW components. The integration results of size exclusion chromatography (SEC) showed that HA increased the NOM removal of Fe(III) and Fe(II) from 10.1 %, 0–14.2 %, 15.2 % and 7.0 %, 5.3–11.0 %, 13.7 % for 1.5–2.5 K MW in OP and JM, respectively. The reasons for the enhanced performance were that, in addition to the reducing effect of HA on Fe redox revealed by cyclic voltammetry, beneficial Fe species were generated, resulting in a greater combination between Fe and organics. In general, this study has provided detailed information about the influence of HA on Fe coagulation when treating NOM and low MW micro-pollutants.
Date Issued
2025-12-01
Date Acceptance
2025-09-13
Citation
Journal of Environmental Chemical Engineering, 2025, 13 (6)
ISSN
2213-3437
Publisher
Elsevier
Journal / Book Title
Journal of Environmental Chemical Engineering
Volume
13
Issue
6
Copyright Statement
Copyright © 2025 Elsevier Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies. This is the author’s accepted manuscript made available under a CC-BY licence in accordance with Imperial’s Research Publications Open Access policy (www.imperial.ac.uk/oa-policy)
License URL
Publication Status
Published
Article Number
119298
Date Publish Online
2025-09-15