Water quality monitoring based on chemometric analysis of high-resolution phytoplankton data measured with flow cytometry.

River water is an important source of Dutch drinking water. For this reason, continuous monitoring of river water quality is needed. However, comprehensive chemical analyses with high-resolution gas chromatography [GC]-mass spectrometry [MS]/liquid chromatography [LC]-MS are quite tedious and time consuming; this makes them poorly fit for routine water quality monitoring and, therefore, many pollution events are missed. Phytoplankton are highly sensitive and responsive to toxicity, which makes them highly usable for effect-based water quality monitoring. Flow cytometry can measure the optical properties of phytoplankton every hour, generating a large amount of information-rich data in one year. However, this requires chemometrics, as the resulting fingerprints need to be processed into information about abnormal phytoplankton behaviour. We developed Discriminant Analysis of Multi-Aspect CYtometry (DAMACY) to model the "normal condition" of the phytoplankton community imposed by diurnal, meteorological, and other exogenous influences. DAMACY first describes the cellular variability and distribution of phytoplankton in each measurement using principal component analysis, and then aims to find subtle differences in these phytoplankton distributions that predict normal environmental conditions. Deviations from these normal environmental conditions indicated abnormal phytoplankton behaviour that happened alongside pollution events measured with the GC/MS and LC/MS systems. Thus, our results demonstrate that flow cytometry in combination with chemometrics may be used for an automated hourly assessment of river water quality and as a near real-time early warning for detecting harmful known or unknown contaminants. Finally, both the flow cytometer and the DAMACY algorithm run completely autonomous and only requires maintenance once or twice per year. The warning system results may be uploaded automatically, so that drinking water companies may temporary stop pumping water whenever abnormal phytoplankton behaviour is detected. In the case of prolonged abnormal phytoplankton behaviour, comprehensive analysis may still be used to identify the chemical compound, its origin, and toxicity.

Determination of backscattering cross section of individual particles from cytometric measurements: a new methodology.

A methodology is developed to derive the backscattering cross section of individual particles as measured with the CytoSense (CytoBuoy b.v., NL). This in situ flow cytometer detects light scatter in forward and sideward directions and fluorescence in various spectral bands for a wide range of particles. First, the weighting functions are determined for the forward and sideward detectors to take into account their instrumental response as a function of the scattering angle. The CytoSense values are converted into forward and sideward scattering cross sections. The CytoSense estimates of uniform polystyrene microspheres from 1 to 90 µm are compared with Mie computations. The mean absolute relative differences ΔE are around 33.7% and 23.9% for forward and sideward scattering, respectively. Then, a theoretical relationship is developed to convert sideward scattering into backscattering cross section, from a synthetic database of 495,900 simulations including homogeneous and multi-layered spheres. The relationship follows a power law with a coefficient of determination of 0.95. To test the methodology, a laboratory experiment is carried out on a suspension of silica beads to compare backscattering cross section as measured by the WET Labs ECO-BB9 and derived from CytoSense. Relative differences are between 35% and 60%. They are of the same order of magnitude as the instrumental variability. Differences can be partly explained by the fact that the two instruments do not measure exactly the same parameter: the cross section of individual particles for the CytoSense and the bulk cross section for the ECO-BB9.

Recommendations on methods for the detection and control of biological pollution in marine coastal waters.

Adverse effects of invasive alien species (IAS), or biological pollution, is an increasing problem in marine coastal waters, which remains high on the environmental management agenda. All maritime countries need to assess the size of this problem and consider effective mechanisms to prevent introductions, and if necessary and where possible to monitor, contain, control or eradicate the introduced impacting organisms. Despite this, and in contrast to more enclosed water bodies, the openness of marine systems indicates that once species are in an area then eradication is usually impossible. Most institutions in countries are aware of the problem and have sufficient governance in place for management. However, there is still a general lack of commitment and concerted action plans are needed to address this problem. This paper provides recommendations resulting from an international workshop based upon a large amount of experience relating to the assessment and control of biopollution.

High frequency monitoring reveals phytoplankton dynamics.

Phytoplankton is an important water quality indicator because of its high species differentiation, growth rates and responsiveness to environmental actuators. The new European Water Framework Directive calls for assessment of the duration, intensity and succession of phytoplankton blooms to determine the ecological status of various types of waters. For common phytoplankton growth rates basic signal processing theory yields a minimum monitoring frequency of once per day, which is much more than applied in standard practice. To assess the nature of this discrepancy we followed the behaviour of about 40 groups of organisms/particles found in the Oude Rijn river by a two-week daily cytometric analysis. Particle counts of the 20 most abundant groups are shown. Their variation rate and magnitude confirm that daily sampling is needed to follow such ecosystems in detail. It is shown that limiting the monitoring to the "coarse line" does not allow a correspondingly decreased sampling frequency. Automated systems may fill the gaps between the microscopical examinations by gathering highly frequent information. The information depth of bulk measurements is poor however, and not used as such. The data shown here demonstrate that modern scanning flow cytometry (SFC) offers an information depth close to the taxonomic level. In the past decade, acquisition and operation costs of these systems have come down considerably, whereas operation is hands free, even in situ and submerged, and data analysis has become more efficient. SFC is used most efficiently complementary to microscopical analyses for mutual validation. In these cases it presents a realistic solution to generate the essential high frequency observations required to assess ecosystem variability.