초록
<P><B>Abstract</B></P> <P>Recent years marked the revitalization of microalgal phytoremediation efforts due to the promise of converting organic-rich effluents into various biofuels and biocommodities, including potential CO<SUB>2</SUB> uptake. In this work, the phytoremediation potential and subsequent production of <I>Chlorella vulgaris</I> biomass containing high added-value metabolites were investigated using thin stillage effluent generated by a starch-based ethanol production plant. A fractional-factorial strategy was developed in order to reveal and understand the variables influencing the investigated process, followed by central composite and response surface methodologies for maximizing the desired outputs. Among process variables such as antibiotic addition, substrate sterilization, pH, light regimes and agitation speed, the latter three manifested the strongest effects on the microalgal proliferation and their phytoremediation efficiency. Further insights on desired process conditions were obtained targeting both maximal effluent treatment and microalgal commodities potentials with minimum operating costs. 85% of total carbon and all of the glycerol, organic acids and carbohydrates were consumed by the microalgae under reduced illumination, pH 6 and 290 rpm after 7 d of cultivation. The <I>Chlorella vulgaris</I> biomass was produced at a rate of 0.9 g/L/d manifesting a high protein content of 32% (w/w) together with 14% (w/w) of carbohydrates and 7% (w/w) of lipids. In addition, natural photosynthetic pigments were generated at a rate of 0.98 mg/L/d (total chlorophylls) and 0.19 mg/L/d (carotenoids). This work highlights the potential of a novel microalgae-based thin stillage phytoremediation process with simultaneous co-generation of high added-value metabolites.</P> <P><B>Highlights</B></P> <P> <UL> <LI> Starch-based thin stillage was used for <I>Chlorella vulgaris</I> cultivation. </LI> <LI> 5 process-variables were screened for their effect on microalgal cultivation. </LI> <LI> pH, light and agitation were optimized for process-output maximization. </LI> <LI> The optimization lead to 85% carbon removal at a biomass productivity of 0.9 g/L/d. </LI> <LI> Simultaneous effluent treatment and microalgal biocommodities were achieved. </LI> </UL> </P> <P><B>Graphical abstract</B></P> <P>[DISPLAY OMISSION]</P>