Advancing Chlorophyll Sensing in Natural Waters: Laser-Induced Fluorescence Spectroscopy with Continuous Poisson Distribution Filtering

The chlorophyll content in water bodies is one of the most important indicator parameters in water quality assessment, red tide warning, carbon cycling, and ecosystem research. Laser-induced fluorescence spectroscopy (LIFS) offers considerable potential for in situ online monitoring of chlorophyll in natural waters. Due to the influence of turbidity, temperature, and suspended algal particles, in situ accurate monitoring of chlorophyll in natural water bodies faces enormous challenges, especially the random movement of suspended algal particles, which often causes the fluctuation amplitude of LIFS signals to be greater than the effective signal, leading to substantial measurement errors. We investigated the impact and patterns of continuous movement of particulate algae within the LIFS measurement field and proposed the continuous Poisson distribution filter (CPDF) to improve the accuracy of LIFS-based chlorophyll sensing in natural waters. By statistically analyzing chlorophyll LIFS signals and implementing the proposed CPDF, the sensing instability is addressed, and the measurement precision is enhanced (the relative magnitude of random fluctuations was reduced from over 33.3% to less than 0.7%). Experiments conducted on wintertime Zhi-Yuan Lake water demonstrate that CPDF can maintain an unbiased proportional relationship between the sensor response and chlorophyll content (p-value < 0.01, R² > 0.99), outperforming conventional frequency-domain filtering and Gaussian-based filters. This research not only advances chlorophyll sensing in aquatic environments but also broadens the application potential of LIFS technology in environmental monitoring, biomedical testing, and many other fields with suspended particulate sensing targets.