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.

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).