Robust off-grid analyser for autonomous remote in-situ monitoring of nitrate and nitrite in water

IF 4.1 Q1 CHEMISTRY, ANALYTICAL
Simon Bluett , Paul O'Callaghan , Brett Paull , Eoin Murray
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引用次数: 4

Abstract

An off-grid, internet-of-things (IoT) connected ion chromatography analyser was developed for the real-time automated measurement of nitrate and nitrite levels in remote surface water applications. The system used KOH eluent with an AG15 guard column to achieve anion separation, in combination with a selective 235 nm UV-LED detector. A self-cleaning 3D printed Sediment Trap was developed to filter the sample before analysis, preventing silt and sediment from causing blockages and facilitating robust performance during long-term deployments. Laboratory tests showed reductions of up to 91% of total suspended solids and 61% of turbidity within the sample after a settling time of 5 min. In controlled temperature tests (7 to 40 °C), the average error in the detected concentration levels remained below 5%, indicating robust and repeatable performance of the analyser in varying environmental conditions. Two automated in-situ analysers were deployed at remote locations in West Cork, Ireland, for a period of one month. The deployments successfully demonstrated the capability of the system to detect transient pollution events, facilitating improved water-quality management of remote catchments. The analysers were monitored in real-time using a cellular IoT module and cloud-based dashboard.

Abstract Image

用于水中硝酸盐和亚硝酸盐自主远程原位监测的鲁棒离网分析仪
开发了一种离网物联网(IoT)连接的离子色谱分析仪,用于远程地表水应用中硝酸盐和亚硝酸盐水平的实时自动测量。该系统使用KOH洗脱液和AG15保护柱来实现阴离子分离,并结合选择性235 nm UV-LED检测器。开发了一种自清洁3D打印沉积物捕集器,用于在分析前过滤样品,防止淤泥和沉积物造成堵塞,并在长期部署期间保持稳定的性能。实验室测试表明,在5分钟的沉淀时间后,样品中悬浮固体总量减少了91%,浊度减少了61%。在受控温度测试(7至40°C)中,检测到的浓度水平的平均误差保持在5%以下,表明该分析仪在不同环境条件下具有稳定且可重复的性能。两台自动现场分析仪被部署在爱尔兰西科克的偏远地区,为期一个月。部署成功地证明了该系统检测瞬时污染事件的能力,有助于改善偏远流域的水质管理。分析仪使用蜂窝物联网模块和基于云的仪表板进行实时监控。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Talanta Open
Talanta Open Chemistry-Analytical Chemistry
CiteScore
5.20
自引率
0.00%
发文量
86
审稿时长
49 days
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