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Updated: Jun 12, 2025

Clean Sampling and Analysis of River and Estuarine Waters for Trace Metal Studies
Published on: July 1, 2016
Fill, Fold, Photo: Preconcentration and Multiplex Detection of Trace Level Heavy Metals in Water
Prakash Aryal1, Jason Boes1, Eric Brack2
1Department of Chemistry, Colorado State University, Fort Collins, Colorado 80523, United States.
Abstract:
Heavy metal contamination is an increasing global threat to human and environmental health, particularly in resource-limited areas. Traditional platforms for heavy metal detection are labor intensive and expensive and require lab facilities. While paper-based colorimetric sensors offer a simpler approach, their sensitivity limitations prevent them from meeting legislative requirements for many metals. Existing preconcentration systems, on the other hand, can achieve lower detection limits but typically focus on analyzing only one metal, making comprehensive monitoring difficult. We address these limitations by introducing a low-cost preconcentration system coupled with colorimetric analysis for the simultaneous detection of seven metal ions at low ppb levels without the need for external equipment outside a smartphone. The system achieved detection limits of 15 ppb (Ni(II)), 7 ppb (Cu(II)), 2 ppb (Fe(III)), 20 ppb (Cr(VI)), 13 ppb (Pb(II)), 26 ppb (Hg(II)), and 15 ppb (Mn(II)) with six out of seven limits of detection values falling well below EPA regulatory guidelines for drinking water. The user-friendly Fill, Fold, Photo approach eliminates complex pretreatment steps. Smartphone-based detection offers portable quantification within seconds. Employing masking strategies ensured higher selectivity for each assay on the card, while our packaging protocols enable system stability for over 4 weeks of study, facilitating mass production and deployment within a realistic time frame. To validate the sensor's performance in real-world scenarios, the sensor was tested with environmental water samples. The sensor demonstrated good recovery, ranging from 77% to 94% compared to the standard ICP-MS method. Furthermore, spike recovery analysis confirmed the sensor's accuracy, with a relative standard deviation (RSD) of less than 15%. This technology holds significant promise for future development as a convenient, portable solution for field-based monitoring of a broad spectrum of water contaminants, including pesticides, PFAS, fertilizers, and beyond.
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