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Biofuels production has been promoted in the attempt to address global warming and oil dependence concerns. However, the environmental impact of biofuels is a very complex issue and cannot be represented by GHG (greenhouse gas) emissions only (carbon footprint). In particular, water consumption (water footprint) has been recognized as a key issue in renewable fuels production. This paper proposes a multiobjective Mixed Integer Linear Programming modeling framework to optimize the environmental (i.e., the carbon and water footprints) and economic performances of bioethanol supply chains. Multiechelon, multiperiod, and spatially explicit features are embedded within the formulation to steer decisions and investments through a global approach. The strategic design and planning of corn- and stover-based bioethanol production networks is taken into account. A case study is presented referring to the emerging Italian ethanol production. Results show the effectiveness of mathematical programming-based tools to provide decision makers with a quantitative analysis assessing the economic and environmental performances of different design configurations. [ABSTRACT FROM AUTHOR]

Understanding the phenomena at interfaces is crucial for producing efficient and stable flexible organic solar cell modules. Minimized energy barriers enable efficient charge transfer, and good adhesion allows mechanical and environmental stability and thus increased lifetime. We utilize here the inverted organic solar module stack and standard photoactive materials (a blend of poly(3-hexylthiophene) and [6,6]-phenyl C61 butyric acid methyl ester) to study the interfaces in a pilot scale large-area roll-to-roll (R2R) process. The results show that the adhesion and work function of the zinc oxide nanoparticle based electron transport layer can be controlled in the R2R process, which allows optimization of performance and lifetime. Plasma treatment of zinc oxide (ZnO) nanoparticles and encapsulation-induced oxygen trapping will increase the absolute value of the ZnO work function, resulting in energy barriers and an S-shaped IV curve. However, light soaking will decrease the zinc oxide work function close to the original value and the S-shape can be recovered, leading to power conversion efficiencies above 3%. We present also an electrical simulation, which supports the results. Finally, we study the effect of plasma treatment in more detail and show that we can effectively remove the organic ligands around the ZnO nanoparticles from the printed layer in a R2R process, resulting in increased adhesion. This postprinting plasma treatment increases the lifetime of the R2R printed modules significantly with modules retaining 80% of their efficiency for ∼3000 h in accelerated conditions. Without plasma treatment, this efficiency level is reached in less than 1000 h., Competing Interests: The authors declare no competing financial interest.