Automated droplet-based microfluidic analyzer for in situ monitoring of ammonium ions in river water
Automated droplet-based microfluidic analyzer for in situ monitoring of ammonium ions in river water
Accurate in situ monitoring of ammonium ion (NH
4
+) levels in water bodies is fundamental for assessing water quality and potential contamination. Here, we present a novel automated droplet-based microfluidic analyzer for in situ monitoring of NH
4
+concentrations in river water. The developed analyzer miniaturizes the modified Berthelot colorimetric method into submicroliter droplets contained within oil flow. The use of droplets enables measurements at high frequency (10 s per measurement) with low reagent consumption (0.3 μL per measurement). NH
4
+measurements showed linear responses up to 2 mg L
–1, and a limit of detection (LOD) of 0.11 mg L
–1. The system was tested with river water samples collected from the River Itchen (Southampton, UK), with excellent agreement (p < 0.05) between the droplet microfluidic analyzer and standard benchtop analysis. The analytical performance of this microfluidic analyzer showed that it could be applicable to sustainable in situ monitoring of NH
4
+levels in a wide range of water bodies and scenarios, including rivers, lakes, aquaculture, and/or industrial effluents.
Droplet microfluidics, colorimetric ammonium detection, continuous monitoring, modified Berthelot method, water quality
4387-4394
Bhuiyan, Wahida Taskin
726b7804-d43d-4516-b7e5-e63f60f03135
Milinovic, Jelena
ce8e4863-495d-4ba2-8f8a-9163541161bf
Warren, Brett
7cb2bba2-fc4e-4d36-b43e-10dfac812195
Liu, Yong-Qiang
75adc6f8-aa83-484e-9e87-6c8442e344fa
Nightingale, Adrian
4b51311d-c6c3-40d5-a13f-ab8917031ab3
Niu, Xize
f3d964fb-23b4-45db-92fe-02426e4e76fa
14 July 2025
Bhuiyan, Wahida Taskin
726b7804-d43d-4516-b7e5-e63f60f03135
Milinovic, Jelena
ce8e4863-495d-4ba2-8f8a-9163541161bf
Warren, Brett
7cb2bba2-fc4e-4d36-b43e-10dfac812195
Liu, Yong-Qiang
75adc6f8-aa83-484e-9e87-6c8442e344fa
Nightingale, Adrian
4b51311d-c6c3-40d5-a13f-ab8917031ab3
Niu, Xize
f3d964fb-23b4-45db-92fe-02426e4e76fa
Bhuiyan, Wahida Taskin, Milinovic, Jelena, Warren, Brett, Liu, Yong-Qiang, Nightingale, Adrian and Niu, Xize
(2025)
Automated droplet-based microfluidic analyzer for in situ monitoring of ammonium ions in river water.
ACS ES&T Water, 5 (8), .
(doi:10.1021/acsestwater.4c01231).
Abstract
Accurate in situ monitoring of ammonium ion (NH
4
+) levels in water bodies is fundamental for assessing water quality and potential contamination. Here, we present a novel automated droplet-based microfluidic analyzer for in situ monitoring of NH
4
+concentrations in river water. The developed analyzer miniaturizes the modified Berthelot colorimetric method into submicroliter droplets contained within oil flow. The use of droplets enables measurements at high frequency (10 s per measurement) with low reagent consumption (0.3 μL per measurement). NH
4
+measurements showed linear responses up to 2 mg L
–1, and a limit of detection (LOD) of 0.11 mg L
–1. The system was tested with river water samples collected from the River Itchen (Southampton, UK), with excellent agreement (p < 0.05) between the droplet microfluidic analyzer and standard benchtop analysis. The analytical performance of this microfluidic analyzer showed that it could be applicable to sustainable in situ monitoring of NH
4
+levels in a wide range of water bodies and scenarios, including rivers, lakes, aquaculture, and/or industrial effluents.
Text
automated-droplet-based-microfluidic-analyzer-for-in-situ-monitoring-of-ammonium-ions-in-river-water
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Accepted/In Press date: 2 July 2025
Published date: 14 July 2025
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Publisher Copyright:
© 2025 The Authors. Published by American Chemical Society
Keywords:
Droplet microfluidics, colorimetric ammonium detection, continuous monitoring, modified Berthelot method, water quality
Identifiers
Local EPrints ID: 505948
URI: http://eprints.soton.ac.uk/id/eprint/505948
ISSN: 2690-0637
PURE UUID: 584fdb85-f9f8-4eb8-aaa6-87bb4494700b
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Date deposited: 23 Oct 2025 17:07
Last modified: 24 Oct 2025 01:46
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Contributors
Author:
Jelena Milinovic
Author:
Brett Warren
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