Copper and lead removal by peanut hulls: equilibrium and kinetic studies

This research work aims to study the use of peanut hulls, an agricultural and food industry waste, for copper and lead removal through equilibrium and kinetic parameters evaluation. Equilibrium batch studies were performed in a batch adsorber. The influence of initial pH was evaluated (3–5) and it was selected between 4.0 and 4.5. The maximum sorption capacities obtained for the Langmuir model were 0.21 ± 0.03 and 0.18 ± 0.02 mmol/g, respectively for copper and lead. In bi-component systems, competitive sorption of copper and lead was verified, the total amount adsorbed being around 0.21 mmol of metal per gram of material in both mono and bi-component systems. In the kinetic studies equilibrium was reached after 200 min contact time using a 400 rpm stirring rate, achieving 78% and 58% removal, in mono-component system, for copper and lead respectively. Their removal follows a pseudo-second-order kinetics. These studies show that most of the metals removal occurred in the first 20 min of contact, which shows a good uptake rate in all systems.

Comparison of allocation approaches in soybean biodiesel life cycle assessment

This work shows the influence of using different allocation approaches when modelling the inventory analysis in a soybean biodiesel life cycle assessment (LCA). Results obtained using mass, energy and economic based allocations are compared, focusing on the following aspects: normalised potential environmental impact (PEI) categories, total PEI and relative contributions to the total PEI from each life cycle stage and environmental impact category. Similar results are obtained either using economic and energy based allocations. However, different results are obtained when mass based allocation is used when compared with the other two. This study also illustrates that using different allocation approaches in biodiesel LCA may influence the final conclusions, especially in comparative assertions, emphasising the need to perform a sensitivity analysis in the LCA interpretation step.