You have no items in your shopping cart.
The professional water quality chlorophyll sensor employs a highly sensitive fluorescence detection principle, enabling wide-range monitoring from 0 to 400 μg/L and 0 to 100 RFU with a resolution as high as 0.1 μg/L. Water quality sensors support RS485/ModBus-RTU communication, self-cleaning optional, offering strong compatibility and easy integration for diverse applications including rivers, lakes, aquaculture, and environmental monitoring.
Submersible Installation
Features NPT 3/4" threads compatible with our waterproof tubing. Route the cable through the tubing and screw the device into the waterproof tube's threads.
Note:
Water quality chlorophyll sensors typically operate based on fluorescence principles. They illuminate chlorophyll molecules in water with light of a specific wavelength, causing them to fluoresce. A detector then receives this fluorescent signal and converts it into chlorophyll concentration. Since fluorescence intensity is directly proportional to chlorophyll content, this enables rapid, continuous online monitoring.
Yes. To ensure measurement accuracy, chlorophyll sensors typically require two-point calibration or zero-point calibration using standard solutions. Regular calibration should be performed based on the application environment, such as every 1–3 months for long-term online monitoring. Calibration steps typically include cleaning the probe, preparing standard solutions, and executing instrument calibration commands. Proper calibration prevents drift caused by optical window contamination or environmental changes.
Chlorophyll measurements may be disrupted by turbidity, suspended solids, bubbles, and biological fouling (algae, debris, etc.). Covered optical windows can cause low readings. Additionally, water temperature fluctuations affect fluorescence intensity, making sensors with temperature compensation more reliable. To minimize errors, regularly clean the probe, avoid vigorous water disturbance, and integrate actual water quality conditions during data analysis.