Evaluation of Analysis Methods for Formaldehyde, Acetaldehyde, and Furfural from Fast Pyrolysis Bio-oil

Fast pyrolysis bio-oil (FPBO), a second-generation liquid bioenergy carrier, is currently entering the market. FPBO is produced from biomass through the fast pyrolysis process and contains a large number of constituents, of which a significant part is still unknown. Various analytical methods have been systematically developed and validated for FPBO in the past; however, reliable methods for characterization of acetaldehyde, formaldehyde, and furfural are still lacking. In this work, different analysis methods with (HS-GC/ECD, HPLC, UV/Vis) and without derivatization (GC/MSD, HPLC) for the characterization of these components were evaluated. Five FPBO samples were used, covering a range of biomass materials (pine wood, miscanthus, and bark), storage conditions (freezer and room temperature), and after treatments (none, filtration, and vacuum evaporation). There was no difference among the methods for the acetaldehyde analysis. A significant difference among the methods for the determination of formaldehyde and furfural was observed. Thus, more data on the accuracy of the methods are required. The precision of all methods was below 10% with the exception of the HPLC analysis of acetaldehyde with an RSD of 14%. The concentration of acetaldehyde in the FPBO produced from the three different biomasses and stored in a freezer after production ranged from 0.24 to 0.60 wt %. Storage at room temperature and vacuum evaporation both decreased significantly the acetaldehyde concentration. Furfural concentrations ranged from 0.11 to 0.36 wt % for the five samples. Storage and after treatment affected the furfural concentration but to a lesser extent than for acetaldehyde. Storage at room temperature decreased formaldehyde similarly to acetaldehyde; however, after vacuum-evaporation the concentration of formaldehyde did not change. Thus, the analysis results indicated that in FPBO the equilibrium of formaldehyde and methylene glycol is almost completely on the methylene glycol side, as in aqueous solutions. All three methods employed here actually measure the sum of free formaldehyde and methylene glycol (FAMG)

Understanding diversity–stability relationships: towards a unified model of portfolio effects

A major ecosystem effect of biodiversity is to stabilise assemblages that perform particular functions. However, diversity–stability relationships (DSRs) are analysed using a variety of different population and community properties, most of which are adopted from theory that makes several restrictive assumptions that are unlikely to be reflected in nature. Here, we construct a simple synthesis and generalisation of previous theory for the DSR. We show that community stability is a product of two quantities: the synchrony of population fluctuations, and an average species-level population stability that is weighted by relative abundance. Weighted average population stability can be decomposed to consider effects of the mean-variance scaling of abundance, changes in mean abundance with diversity and differences in species' mean abundance in monoculture. Our framework makes explicit how unevenness in the abundances of species in real communities influences the DSR, which occurs both through effects on community synchrony, and effects on weighted average population variability. This theory provides a more robust framework for analysing the results of empirical studies of the DSR, and facilitates the integration of findings from real and model communities