The citizen scientists’ laboratory—quantifying copper in drinking water
Safely managed drinking water is of utmost importance. Citizen scientists have been successful in collecting water monitoring data worldwide. However, in these projects, test strips or colorimetric assays have usually been used. The implementation of laboratory methods within a citizen science project could confer both benefits and risks regarding the data collected. We, therefore, compared citizen scientists’ data collected using either a colorimetric method or a spectrophotometric method. The citizen scientists’ data (n = 456) were evaluated by comparing these data with reference data obtained from external laboratory analyses. Citizen scientists’ colorimetric data were highly correlated and showed a moderate percentage agreement with the reference data (percentage agreement: 60%; Spearman r = 0.671). The percentage agreement was, however, poor for drinking water samples that contained larger amounts of copper when the citizen scientists used a colorimetric method. Data from the same samples obtained by the citizen scientists using a spectrophotometric laboratory method were also compared with the reference data and showed a slightly higher percentage agreement and stronger correlation with the reference data (percentage agreement: 69%; Spearman r = 0.727). The percentage agreement was consistent for samples that contained different amounts of copper when the citizen scientists used a spectrophotometric method. The data indicated that citizen science projects could improve data quality by involving citizen scientists in laboratory work.
Authors
- Vanessa van den Bogaert (ORCID: https://orcid.org/0000-0001-8002-9134)
- Jan Kath
- Katrin Sommer (ORCID: https://orcid.org/0000-0002-1768-0968)
- Christian G. Strippel (ORCID: https://orcid.org/0000-0001-9806-7446)
- Joachim Wirth
Institutions
- Leibniz University Hannover (DE)
- Ruhr University Bochum (DE)
Publication Details
- Journal
- Frontiers in Environmental Science
- Published
- 2026-03-02
- DOI
- https://doi.org/10.3389/fenvs.2026.1765827
- Primary Topic
- Biosensors and Analytical Detection
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Bundesministerium für Bildung und Forschung