Toward scalable freshwater monitoring: an open-source sensor for chlorophyll-a fluorescence and turbidity

Freshwater monitoring programs increasingly require affordable, field-deployable, and reliable sensors to expand the spatial and temporal coverage of key water quality indicators such as chlorophyll-a. However, data quality concerns currently limit the integration of community-based observations into operational monitoring frameworks, and the reliability of many low-cost technologies remains constrained by limited validation and inconsistent reporting practices. This work presents the design and validation of an open-source portable fluorescence sensor for the simultaneous quantification of chlorophyll-a and turbidity in freshwater systems. The proposed optical sensor integrates automated signal processing and IoT-enabled data transmission within a compact system costing less than US$100. Analytical performance was assessed under laboratory, mesocosm conditions. In vitro calibration demonstrated a linear response for chlorophyll-a over the 1–100 µg L−1 range (R2 = 0.987–0.999), with limits of detection and quantification of 0.12 and 0.28 µg L−1, respectively. Within the 6–100 µg L−1 working range, mean relative bias remained below 15%. Turbidity measurements showed a mean relative bias below 12% in the 10–150 NTU range, with a LOQ of 7.28 NTU. Instrument stability was maintained over a three-month evaluation period, with calibration slope variability below 9% RSD. In vivo testing on natural river samples showed strong agreement with a benchtop spectrofluorometer (R2 = 0.95), and regression-based calibration across 59 samples reduced relative bias from 26.5% to 2.99% and RMSE from 12.7 to 5.3 µg L−1, confirmed by 5-fold cross-validation. The proposed sensor offers a scalable and reproducible approach for integrating low-cost optical sensing into distributed freshwater monitoring frameworks. This journal is © The Royal Society of Chemistry, 2026.