Advancing Community-Based Water Quality Monitoring through Low-Cost Open-Source Optical Sensors and Data Integration

To meet European (WFD) and International objectives (SDGs), there is a growing demand for water quality data with elevated spatial and temporal resolution. This has been an ongoing process, achieved by integrating data from governmental agencies with community-based monitoring initiatives (crowdsensing). Community-based monitoring has proven effective in addressing information gaps in managing and monitoring aquatic ecosystems, particularly in small rivers that often lack agency monitoring. However, there are still challenges regarding the reliability of such data. To fill this gap, there is an urgent need to develop affordable, reliable, and open-source instrumentation for water quality monitoring. These instruments should also comply with the recent European guidelines on the use of toxic substances in technology development.

This study presents the development and validation of a RoHS directive-compliant, open-source, low-cost optical sensor for detecting nitrates and phosphates in community-based monitoring initiatives. The sensor setup takes advantage of light-emitting diodes (LED) as light sources and a commercial ambient light detector. A second light sensor positioned at a 90° angle is employed for scattering correction. All components are managed by a Raspberry Pi Zero W microcomputer and housed in a custom 3D-printed poly(lactic acid) case. The device enables data collection, including GPS coordinates, with results stored offline or transmitted in real-time through Wi-Fi. The sensor’s analytical performance was evaluated in both laboratory and field conditions using reference materials and river samples. Results demonstrated accurate and repeatable measurements which were shown to increase resolution and precision compared to standard colorimetric methods. To promote accessibility and replication, the 3D-box CAD model, software, and usage guidelines are freely available online.