Implications of irradiance exposure and non-photochemical quenching for multi-wavelength (bbe FluoroProbe) fluorometry

Chlorophyll a estimation in lakes using multi-parameter sonde data

Algae blooms are of considerable concern in freshwater lakes and reservoirs worldwide. In-situ Chlorophyll a (Chl-a) fluorometers are widely used for rapid assessments of algae biomass. However, accurately converting Chl-a fluorescence to an equivalent concentration is challenging due to natural variations in the relationship as well as nonphotochemical quenching (NPQ) which occurs commonly in surface waters during daytime. This study is based on water quality data from a freshwater lake from October 2018 to December 2020. Initial analysis of sonde Chl-a fluorescence and laboratory extracted Chl-a concentrations shows that the two data sets exhibit a nonlinear relationship with positive correlation and significant errors. A bias correction method was next developed based on (1) concurrent sonde measurements of other water quality parameters (to account for nonlinearities) and (2) a bias correction approach for nonphotochemical quenching effects in surface waters. The new Chl-a model exhibits much improved accuracy, with a root mean square error (RMSE) less than 0.95 µg/L. The new method facilitates accurate Chl-a characterization in freshwater lakes and reservoirs based on readily obtainable in-situ fluorescence sonde measurements.

Effectiveness of a fixed-depth sensor deployed from a buoy to estimate water-column cyanobacterial biomass depends on wind speed

Water quality sondes have the advantage of containing multiple sensors, extended deployment times, high temporal resolution, and telecommunication with stakeholder accessible data portals. However, sondes that are part of buoy deployments often suffer from typically being fixed at one depth. Because water treatment plants are interested in water quality at a depth of the water intake and other stakeholders (ex. boaters and swimmers) are interested in the surface, we examined whether a fixed depth of approximately 1 m could cause over- or under-estimation of cyanobacterial biomass. We sampled the vertical distribution of cyanobacteria adjacent to a water quality sonde buoy in the western basin of Lake Erie during the summers of 2015-2017. A comparison of buoy cyanobacteria RFU (Relative Fluorescence Unit) at 1 m to cyanobacteria chlorophyll a (chla) measured throughout the water column showed occurrences when the buoy both under and overestimated the cyanobacteria chla at specific depths. Largest differences between buoy measurements and at-depth grab samples occurred during low wind speeds (< 4.5 m/sec) because low winds allowed cyanobacteria to accumulate at the surface above the buoy's sonde. Higher wind speeds (> 4.5 m/sec) resulted in better agreement between the buoy and at-depth measurements. Averaging wind speeds 12 hr before sample collection decreased the difference between the buoy and at-depth samples for high wind speeds but not low speeds. We suggest that sondes should be placed at a depth of interest for the appropriate stakeholder group or deploy sondes with the ability to sample at various depths.

An ecotoxicological view on neurotoxicity assessment

The numbers of potential neurotoxicants in the environment are raising and pose a great risk for humans and the environment. Currently neurotoxicity assessment is mostly performed to predict and prevent harm to human populations. Despite all the efforts invested in the last years in developing novel in vitro or in silico test systems, in vivo tests with rodents are still the only accepted test for neurotoxicity risk assessment in Europe. Despite an increasing number of reports of species showing altered behaviour, neurotoxicity assessment for species in the environment is not required and therefore mostly not performed. Considering the increasing numbers of environmental contaminants with potential neurotoxic potential, eco-neurotoxicity should be also considered in risk assessment. In order to do so novel test systems are needed that can cope with species differences within ecosystems. In the field, online-biomonitoring systems using behavioural information could be used to detect neurotoxic effects and effect-directed analyses could be applied to identify the neurotoxicants causing the effect. Additionally, toxic pressure calculations in combination with mixture modelling could use environmental chemical monitoring data to predict adverse effects and prioritize pollutants for laboratory testing. Cheminformatics based on computational toxicological data from in vitro and in vivo studies could help to identify potential neurotoxicants. An array of in vitro assays covering different modes of action could be applied to screen compounds for neurotoxicity. The selection of in vitro assays could be guided by AOPs relevant for eco-neurotoxicity. In order to be able to perform risk assessment for eco-neurotoxicity, methods need to focus on the most sensitive species in an ecosystem. A test battery using species from different trophic levels might be the best approach. To implement eco-neurotoxicity assessment into European risk assessment, cheminformatics and in vitro screening tests could be used as first approach to identify eco-neurotoxic pollutants. In a second step, a small species test battery could be applied to assess the risks of ecosystems.