Environmental fluorescence measurements sometimes use water Raman scattering as an internal standard to compensate for path length, lensing effects, and turbidity. Fluorescent dissolved organic matter (FDOM) in water may interfere strongly with the measurement of this reference. However, fluorescence in fluid solution is largely unpolarized, while the OH stretching Raman band of water is always strongly polarized. Using an environmental sample from Lake Wateree in South Carolina, USA, we demonstrate that judicious use of this polarization allows for a significant level of improvement in the contrast or visibility of the water Raman band relative to FDOM.

This experiment uses a research grade Raman microscope system to measure the energy difference between the higher energy cis- and lower energy trans-isomers of N-methylformamide (NMF). The experimental portion of this work involves measuring the intensities of key Raman bands associated with each of the two isomeric forms of NMF as a function of the temperature. A van't Hoff plot showing the temperature dependence of the equilibrium is used to estimate the standard change in enthalpy (Delta H degrees) for the reaction. A value of 5.90 +/- 0.15 kJ/mol (95% C.I.) for the isomerization of trans to cis was obtained for a set of example data reported. An average over multiple semesters and multiple experimental groups was 6.65 +/- 0.86 kJ/mol (s.d.). This compares to four experimental literature values ranging from 3.71-7.44 kJ/mol.

We describe the control and interfacing of a fluorometer designed for aerial drone-based measurements of chlorophyll-a using an Arduino Nano 33 BLE Sense board. This 64 MHz controller board provided suitable resolution and speed for analog-to-digital (ADC) conversion, processed data, handled communications via the Robot Operating System (ROS) and included a variety of built-in sensors that were used to monitor the fluorometer for vibration, acoustic noise, water leaks and overheating. The fluorometer was integrated into a small Uncrewed Aircraft System (sUAS) for automated water sampling through a Raspberry Pi master computer using the ROS. The average power consumption was 1.1 W. A signal standard deviation of 334 µV was achieved for the fluorescence blank measurement, mainly determined by the input noise equivalent power of the transimpedance amplifier. An ADC precision of 130 µV for 10 Hz chopped measurements was achieved for signals in the input range 0-600 mV.

Uncrewed Aircraft Systems (UAS) are increasingly used in time-consuming and effort-heavy scientific exploration applications. One such application is the inspection of the physical, chemical, and biological properties of water in aquatic ecosystems. This paper presents a novel autonomous UAS capable of sensing water properties and collecting up to three 250 mL water samples from multiple sampling locations. The system features a customized UAS with an in-house built fluorescence sensor and pumping mechanism. The system does in situ fluorescence measurements to map the gradient of fluorescent content across the body of water and determine the best sampling spot for targeted sampling. To ensure safe near-water operation, multiple sensor fusion with an Extended Kalman Filter has been implemented for accurate altitude estimation within 1.5 m from the water surface. To validate the performance of the system, we present experimental results from deployment in two different water ecosystems, namely the Congaree River, SC and Lake Wateree, SC.

We recently described a lightweight, low-power, waterproof filter fluorometer using a 180° backscatter geometry for chlorophyll-a (chl-a) detection. Before it was constructed it was modeled to ensure it would have satisfactory performance. This manuscript repeats the modeling process that allows the calibration slope and detection limit for a fluorescent analyte in water to be estimated from system component performance and conventional spectrofluorometry alone. These values are validated by comparison to the experimental result of calibration from the completed instrument. Our model yields a calibration slope of 8.22 mV-L/µg for dissolved chl-a, consistent with the experimentally measured slope of 8.21 mV-L/µg. The detection limit modeled from this slope and an estimate of the baseline noise of the instrument was 0.15 µg/L chl-a, while the measured detection limit using real blank samples was 0.18 µg/L, in 0.1 s differential measurements.

In this short overview, we consider use cases for diffuse reflection spectroscopy and introduce the Kubelka-Munk diffuse reflectance formula. We conclude by comparing diffuse transmittance, diffuse reflectance, logarithmic transforms of both, and the Kubelka-Munk transform for mid-infrared spectroscopy of the same sample.

We describe a waterproof, lightweight (1.3 kg), low-power (∼1.1 W average power) fluorometer operating on 5 V direct current deployed on a small uncrewed aircraft system (sUAS) to measure chlorophyll and used for triggering environmental water sampling by the sUAS. The fluorometer uses a 450 nm laser modulated at 10 Hz for excitation and a standard photodiode and transimpedance amplifier for the detection of fluorescence. Additional detectors are available for measuring laser intensity and light scattering. Control of the fluorometer and communication between the fluorometer and the Raspberry Pi 4B computer controlling the sampler were provided by an Arduino microcontroller using the robot operating system (ROS). Calibrations were based on standards of dissolved chlorophyll extracted from Chlorella powder (a widely available dietary supplement). The detection limit for chlorophyll from these calibrations was found to be 0.2 μg per liter of water for a single 0.1 s differential measurement. The detection limit decreases with the square root of the integration time as expected. Detection limits increase by a factor of two to three when mounted in the sUAS due to electrical noise; sUAS acoustic noise and vibration do not appear to contribute significantly.

Water sensing and sampling is a complex application that can benefit from the use of aerial drones. In the monitoring of an aquatic environment, inspection of its physical, chemical, and biological states are equally important. In most cases, only the physical and chemical properties are investigated due to lack of portable sensor packages capable of in situ measurements of biological indicators. Additionally, biological sample collection for ex situ analysis poses certain challenges which requires specialized sample collection methods. For acquiring a good sample, remote sensing needs to work hand in hand with the sampling mechanism to capture the correct analyte of interest. This work presents the design and development of an aerial drone equipped with a custom-made sensor package and sampling mechanism, for sensing and non-destructive sampling of dissolved organic matter in aquatic environments. The developed system is experimentally validated in an outdoor setting and is shown to be capable for in situ measurements of fluorescent content of water bodies and sensor-triggered sample collection.

Mission planning for small uncrewed aerial systems (sUAS) as a platform for remote sensors goes beyond the traditional issues of selecting a sensor, flying altitude/speed, spatial resolution, and the date/time of operation. Unlike purchasing or contracting imagery collections from traditional satellite or manned airborne systems, the sUAS operator must carefully select launching, landing, and flight paths that meet both the needs of the remote sensing collection and the regulatory requirements of federal, state, and local regulations. Mission planning for aerial drones must consider temporal and geographic changes in the environment, such as local weather conditions or changing tidal height. One key aspect of aerial drone missions is the visibility of the aircraft and communication with the aircraft. In this research, a visibility model for low-altitude aerial drone operations was designed using a GIS-based framework supported by high spatial resolution LiDAR data. In the example study, the geographic positions of the visibility of an aerial drone used for water sampling at low altitudes (e.g., 2 m above ground level) were modeled at different levels of tidal height. Using geospatial data for a test-case environment at the Winyah Bay estuarine environment in South Carolina, we demonstrate the utility, challenges, and solutions for determining the visibility of a very low-altitude aerial drone used in water sampling.

Part 1 of this three-part series provided a procedure for quickly recording acceptable fluorescence spectra with classic commercial spectrofluorometers for most samples in common 1- cm-pathlength cuvettes. Part 2 of the series describes instrument-specific concerns that require modifications to our initial procedure if we want spectra that can be accurately reproduced in other laboratories. Part 3 will discuss how the sample itself can make reproducibility between instruments challenging."

The first installment of this three-part series provided a procedure for quickly recording acceptable fluorescence spectra with classic commercial spectrofluorometers for most samples in common 1-cm pathlength cuvettes. Part 2 described how to correct for instrument response so data can be compared properly between laboratories. This part describes sample-specific concerns that could require modifications of our basic procedure to prevent our data from being inconsistent.

This article is the first of a 3-part series that gives a procedure to avoid common errors in spectrofluorometry using an example case. Part 2 will focus on throughput and polarization correction of spectrofluorometers for the purpose of inter-laboratory comparisons, while Part 3 will focus on non-ideal sample behavior.