Automated high-temporal-resolution multi-element river water monitoring with ICP-MS

Real-time monitoring of multi-element concentrations in rivers is highly desirable due to potential hazardous impacts and a better understanding of geochemical cycles. Most of the available datasets are generated from low-frequency sampling (weekly or monthly), include only a limited number of elements, and fail to capture rapid changes and short-term events occurring between two sampling dates. Relying on such sparse data limits our understanding of the behavior of elements and their temporal changes within catchments. In consequence, this leads to inaccuracies in mass balance calculations and a loss of awareness for sudden pollution events. Thus, there is an urgent need for continuous fully quantitative high-temporal-resolution multi-element monitoring of river water to provide comprehensive datasets to improve water management, also with respect to machine learning training and prognosis. Therefore, we developed an automated atline method using inductively coupled plasma-mass spectrometry (ICP-MS) to continuously measure 56 elements in river water at a high time resolution of one mixed sample per hour. To achieve this, we constructed a self-cleaning fraction Collector/AuTosampler system (CAT) which continuously collects and provides samples (24/7) to the ICP-MS. The CAT was coupled with an ICP-QMS and an ICP-QQQ-MS which were, for the first time, fully automated and fully quantitative operated in river water monitoring using a Python script. Our results provided hourly concentrations of 56 elements in the Rhine River (Germany) for a period of 1 month and allowed to investigate short-term events such as high river discharge and their impacts on element concentrations. The time series of continuously measured electrical conductivity and the major elements indicated a similar variability. The results also highlight potential inaccuracies caused by using only low-frequency sampling that can accumulate in annual estimates. The fully automated atline high-resolution monitoring approach is delivered completely and transparently in this study and represents a breakthrough in element monitoring automation, offering a valuable tool to understand complex element behaviors and to detect rapid changes in river water in close to real time.

Authors

Institutions

Publication Details

Journal
Environmental Sciences Europe
Published
2025-06-07
DOI
https://doi.org/10.1186/s12302-025-01131-8
Citations
2
Primary Topic
Water Quality Monitoring and Analysis
Type
article
Field-Weighted Citation Impact
1.99
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Automated high-temporal-resolution multi-element river water monitoring with ICP-MS

Julia Arndt, Thomas A. Ternes, Lars Duester, Jan G. Wiederhold et al.
2 citations
Environmental Sciences Europe
Water Quality Monitoring and Analysis
1.99
article

Automated high-temporal-resolution multi-element river water monitoring with ICP-MS

Julia Arndt, Thomas A. Ternes, Lars Duester, Jan G. Wiederhold, Alex Zavarsky, Mohamed Harhash, Ingrid Nett
article en
2 citations

Abstract

Real-time monitoring of multi-element concentrations in rivers is highly desirable due to potential hazardous impacts and a better understanding of geochemical cycles. Most of the available datasets are generated from low-frequency sampling (weekly or monthly), include only a limited number of elements, and fail to capture rapid changes and short-term events occurring between two sampling dates. Relying on such sparse data limits our understanding of the behavior of elements and their temporal changes within catchments. In consequence, this leads to inaccuracies in mass balance calculations and a loss of awareness for sudden pollution events. Thus, there is an urgent need for continuous fully quantitative high-temporal-resolution multi-element monitoring of river water to provide comprehensive datasets to improve water management, also with respect to machine learning training and prognosis. Therefore, we developed an automated atline method using inductively coupled plasma-mass spectrometry (ICP-MS) to continuously measure 56 elements in river water at a high time resolution of one mixed sample per hour. To achieve this, we constructed a self-cleaning fraction Collector/AuTosampler system (CAT) which continuously collects and provides samples (24/7) to the ICP-MS. The CAT was coupled with an ICP-QMS and an ICP-QQQ-MS which were, for the first time, fully automated and fully quantitative operated in river water monitoring using a Python script. Our results provided hourly concentrations of 56 elements in the Rhine River (Germany) for a period of 1 month and allowed to investigate short-term events such as high river discharge and their impacts on element concentrations. The time series of continuously measured electrical conductivity and the major elements indicated a similar variability. The results also highlight potential inaccuracies caused by using only low-frequency sampling that can accumulate in annual estimates. The fully automated atline high-resolution monitoring approach is delivered completely and transparently in this study and represents a breakthrough in element monitoring automation, offering a valuable tool to understand complex element behaviors and to detect rapid changes in river water in close to real time.

Environmental Sciences EuropeVol. 37(1)
Federal Institute of Hydrology (DE)
Clean water and sanitation
Openalex Percentile: Top 14%
Water Quality Monitoring and Analysis
1.99
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.