Fluvial biofilms: a pertinent tool to assess β-blockers toxicity

Among increasingly used pharmaceutical products, β-blockers have been commonly reported at low concentrations in rivers and littoral waters of Europe and North America. Little is known about the toxicity of these chemicals in freshwater ecosystems while their presence may lead to chronic pollution. Hence, in this study the acute toxicity of 3 β-blockers: metoprolol, propranolol and atenolol on fluvial biofilms was assessed by using several biomarkers. Some were indicative of potential alterations in biofilm algae (photosynthetic efficiency), and others in biofilm bacteria (peptidase activity, bacterial mortality). Propranolol was the most toxic β-blocker, mostly affecting the algal photosynthetic process. The exposure to 531 μg/L of propranolol caused 85% of inhibition of photosynthesis after 24 h. Metoprolol was particularly toxic for bacteria. Though estimated No-Effect Concentrations (NEC) were similar to environmental concentrations, higher concentrations of the toxic (503 μg/L metoprolol) caused an increase of 50% in bacterial mortality. Atenolol was the least toxic of the three tested β-blockers. Effects superior to 50% were only observed at very high concentration (707 mg/L). Higher toxicity of metoprolol and propranolol might be due to better absorption within biofilms of these two chemicals. Since β-blockers are mainly found in mixtures in rivers, their differential toxicity could have potential relevant consequences on the interactions between algae and bacteria within river biofilms

Monitoring procedures in environmental geochemistry and compositional data analysis theory

First discussion on compositional data analysis is attributable to Karl Pearson, in 1897. However, notwithstanding the recent developments on algebraic structure of the simplex, more than twenty years after Aitchison’s idea of log-transformations of closed data, scientific literature is again full of statistical treatments of this type of data by using traditional methodologies. This is particularly true in environmental geochemistry where besides the problem of the closure, the spatial structure (dependence) of the data have to be considered. In this work we propose the use of log-contrast values, obtained by a simplicial principal component analysis, as LQGLFDWRUV of given environmental conditions. The investigation of the log-constrast frequency distributions allows pointing out the statistical laws able to generate the values and to govern their variability. The changes, if compared, for example, with the mean values of the random variables assumed as models, or other reference parameters, allow defining monitors to be used to assess the extent of possible environmental contamination. Case study on running and ground waters from Chiavenna Valley (Northern Italy) by using Na+, K+, Ca2+, Mg2+, HCO3-, SO4 2- and Cl- concentrations will be illustrated