A field-deployable and handheld fluorometer for environmental water quality monitoring
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This work reports the development of a field-deployable and fully handheld fluorometer for environmental water monitoring. Our developed fluorimeter can detect both green algae and cyanobacteria (blue-green algae) while simultaneously differentiating and measuring two different species by selectively measuring chlorophyll a fluorescence from green algae and phycocyanin fluorescence from blue-green algae. As a demonstration, chlorophyll a and phycocyanin photopigments were estimated and differentiated. The system was also tested with an environmental water sample collected from a lake to validate the system functionality. The presented results suggest that our developed fluorimeter could be used as a portable water quality monitoring system for detection of different photopigment of algae.
KeywordsGreen algae Blue-green algae (cyanobacteria) Water quality monitoring Fluorometer
Distribution of phytoplankton groups provides important information about the environmental water quality because they are closely related with eutrophic status which often caused by the water contamination . Rapid reproduction of algae in waterbody due to the inflow of nutrient containing nitrogen (N) and phosphorus (P) causes hypoxia that kills marine animals and disrupts the aquatic ecosystems. Some cyanobacteria (blue-green algae) species even produce cytotoxic substances that could pose problem for those of who get their drinking water from lakes or reservoirs contacting toxic blooms. Current widely used methods in phytoplankton detection and classification are microscopic examination , high-performance liquid chromatography (HPLC) , and bench-top flow-cytometry  which are time-consuming, expensive, and difficult to apply for the on-field detection. Fluorimetry is one of the widely used tools in detecting and analyzing different phytoplankton species by measuring the fluorescence signals emitted from the photopigments .
Previously, we have reported a fluorometer system in [6, 7] based on controlled samples. In this work, we demonstrate the functionality of our system at a local lake using environmental water samples collected on site. A hand-held fluorometer has three different wavelengths of excitation light emitting diodes (LEDs) to selectively stimulate the target phytoplankton species and corresponding fluorescence signal was measured with a photodetector. Electronic system including the microcontroller unit, liquid crystal display (LCD), and data storage unit are compactly assembled into a custom-made 3D-printed jig.
A schematic illustration of our fluorometer system is shown in Fig. 1b. Three different wavelengths of excitation LEDs are used to selectively stimulate the distinct photopigment of target species. A blue LED (448 nm) is used to stimulate chlorophyll a in microalgae while amber LED (590 nm) is used to stimulate phycocyanin in blue-green algae [8, 9]. An ultraviolet (UV) LED (360 nm) is used to stimulate both chlorophyll a and phycocyanin pigments. Three LEDs are implemented and sequentially turned on and off to selectively excite each pigment, and the corresponding fluorescence signals were measured with a highly sensitive silicon photomultiplier (SiPM). Two long-pass filters are mounted on top of the SiPM photosensor to block the excitation light while only allowing the longer wavelength fluorescence to pass. A 20 µl aliquot of the sample solution is easily delivered with a disposable glass micro-vial.
Materials and methods
Chlorophyll a and phycocyanin fluorescence experiments
For the sample preparation, 1 mg of chlorophyll a powder (Sigma-Aldrich, MO, USA) was dissolved into a diethyl ether solvent (VWR, PA, USA) and 10.0 mg ml−1 of phycocyanin (Sigma-Aldrich, MO, USA) was mixed with deionized (DI) water. Sample stocks at a lower concentration were obtained by serially diluting the highest solution stocks for each pigment.
For measuring fluorescence signals of chlorophyll a and phycocyanin, glass micro-vials were filled with different concentrations of 20 µl sample volume. The measurements were conducted with three replicates of glass micro-vials for each concentration. An empty micro-vial was placed on the sensing aperture of the device and the sample solution was loaded into the vial. A light blocker cap was closed to block the ambient light noise. The LEDs were set to emit light intensity of 0.6 µE m−2 s−1 (or 122 m Wm−2), 0.5 µE m−2 s−1 (or 109 m Wm−2), and 0.35 µE m−2 s−1 (or 134 m Wm−2) for the amber, UV, and blue excitation LEDs, respectively.
Results and discussion
Characterization of chlorophyll a and phycocyanin fluorescence
Characterization of green algae and blue-green algae fluorescence
Identification of chlorophyll a and phycocyanin in a local lake water
The results of chlorophyll a and phycocyanin pigments estimated by measuring samples that are collected from the local lake
Test 1 (µg l−1)
Test 2 (µg l−1)
Test 3 (µg l−1)
Overall (µg l−1)
25.0 ± 1.0
4.3 ± 0.6
In this work, we have developed a field-deployable handheld fluorimeter that could monitor the environmental water quality by detecting and distinguishing different photopigments of phytoplankton species. Green algae were detected by the chlorophyll a fluorescence under the blue LED excitation and blue-green algae were detected by the phycocyanin fluorescence under the amber LED excitation. Each LED was sequentially turned on and off and corresponding fluorescence signals were measured by the highly sensitive silicon photomultiplier. Future work will include implementing additional wavelengths of excitation LEDs to broaden the range of excitation wavelength and a monochromator to scan the wide range of fluorescence emission wavelength.
YHS and JWC designed the research and experiments. MTGW cultured the sample and supported characterization. YHS and MTGW analyzed the data. YSH wrote the paper. JWC supervised the research and preparation of the manuscript. All authors read and approved the final manuscript.
The authors declare that they have no competing interests.
Availability of data and materials
The datasets supporting the conclusions of this article are included within the article.
This research was supported in part by National Science Foundation EPSCoR and Louisiana Board of Regents, Contract LEQSF-EPS(2014)-PFUND-347.
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