Effects of various pollutant mixtures on immune responses of the blue mussel (Mytilus edulis) collected at a salinity gradient in Danish coastal waters, links to supplementary material

The Baltic Sea is a semi-enclosed sea with a steady salinity gradient (3 per mil-30 per mil). Organisms have adapted to such low salinities, but are suspected to be more susceptible to stress. Within the frame of the integrated environmental monitoring BONUS + project "BEAST" the applicability of immune responses of the blue mussel was investigated in Danish coastal waters. The sampling sites were characterised by a salinity range (11-19 per mil) and different mixtures of contaminants (metals, PAHs and POPs), according to chemical analysis of mussel tissues. Variation partitioning (redundancy analysis) was applied to decompose salinity and contamination effects. The results indicated that cellular immune responses (total and differential haemocyte count, phagocytic activity and apoptosis) were mainly influenced by contaminants, whereas humoral factors (haemolytic activity) were mainly impacted by salinity. Hence, cellular immune functions may be suitable as biomarkers in monitoring programmes for the Baltic Sea and other geographic regions with salinity variances of the studied range.

Current velocities and settling experimental results

This study provides a theoretical assessment of the potential bias due to differential lateral transport on multi-proxy studies based on a range of marine microfossils. Microfossils preserved in marine sediments are at the centre of numerous proxies for paleoenvironmental reconstructions. The precision of proxies is based on the assumption that they accurately represent the overlying watercolumn properties and faunas. Here we assess the possibility of a syn-depositional bias in sediment assemblages caused by horizontal drift in the water column, due to differential settling velocities of sedimenting particles based on their shape, size and density, and due to differences in current velocities. Specifically we calculate the post-mortem lateral transport undergone by planktic foraminifera and a range of other biological proxy carriers (diatoms, radiolaria and fecal pellets transporting coccolithophores) in several regions with high current velocities. We find that lateral transport of different planktic foraminiferal species is minimal due to high settling velocities. No significant shape- or size-dependent sorting occurs before reaching the sediment, making planktic foraminiferal ideal proxy carriers. In contrast, diatoms, radiolaria and fecal pellets can be transported up to 500 km in some areas. For example in the Agulhas current, transport can lead to differences of up to 2°C in temperature reconstructions between different proxies in response to settling velocities. Therefore, sediment samples are likely to contain different proportions of local and imported particles, decreasing the precision of proxies based on these groups and the accuracy of the temperature reconstruction.

Density of alkyl esters and its mixtures

Biodiesel density is a key parameter in biodiesel simulations and process development. In this work we selected, evaluated and improved two density models, one theoretical (Rackett-Soave) and one empirical (Lapuerta's method) for methanol based biodiesels (FAME) and ethanol based biodiesel (FAEE). For this purpose, biodiesel was produced from vegetable oils (sunflower, rapeseed, soybean, olive, safflower and other two commercial mixtures of vegetable oils) and animal fats (edible and crude pork fat and beef tallow) using both methanol and ethanol for the transesterification reactions, and blended to get 21 FAME and 21 FAEE, reporting their density and detailed composition. Bibliographic data have also been used. The Rackett-Soave method has been improved by the use of a new acentric factor correlation, whereas the parameters of the empirical one are improved by considering a bigger density data bank. Results show that the evaluated models could be used to estimate the biodiesel density with a good grade of accuracy but the performed modifications improve the accuracy of the models: ARD (%) for FAME; 0.33, and FAEE; 0.26, both calculated with the modification of Rackett-Soave method and ARD (%) for FAME; 0.40 calculated with the modification of the Lapuerta's method).

Particle camera and settling chamber measurements at site PC (GeoB11834-3) and SC (GeoB12914-4) off Cape Blanc/Mauritania

Particles sinking out of the euphotic zone are important vehicles of carbon export from the surface ocean. Most of the particles produce heavier aggregates by coagulating with each other before they sink. We implemented an aggregation model into the biogeochemical model of Regional Oceanic Modelling System (ROMS) to simulate the distribution of particles in the water column and their downward transport in the Northwest African upwelling region. Accompanying settling chamber, sediment trap and particle camera measurements provide data for model validation. In situ aggregate settling velocities measured by the settling chamber were around 55 m d**-1. Aggregate sizes recorded by the particle camera hardly exceeded 1 mm. The model is based on a continuous size spectrum of aggregates, characterised by the prognostic aggregate mass and aggregate number concentration. Phytoplankton and detritus make up the aggregation pool, which has an averaged, prognostic and size dependent sinking. Model experiments were performed with dense and porous approximations of aggregates with varying maximum aggregate size and stickiness as well as with the inclusion of a disaggregation term. Similar surface productivity in all experiments has been generated in order to find the best combination of parameters that produce measured deep water fluxes. Although the experiments failed to represent surface particle number spectra, in the deep water some of them gave very similar slope and spectrum range as the particle camera observations. Particle fluxes at the mesotrophic sediment trap site off Cape Blanc (CB) have been successfully reproduced by the porous experiment with disaggregation term when particle remineralisation rate was 0.2 d**-1. The aggregation-disaggregation model improves the prediction capability of the original biogeochemical model significantly by giving much better estimates of fluxes for both upper and lower trap. The results also point to the need for more studies to enhance our knowledge on particle decay and its variation and to the role that stickiness play in the distribution of vertical fluxes.