Fernando G. Martins

TL;DR: In this article, the authors review the recent developments on the carbon capture and storage (CCS) methodologies from 2006 until now, focusing on the basic findings achieved in CCS operational projects.

TL;DR: Predicting next day hourly ozone concentrations through a new methodology based on feedforward artificial neural networks using principal components as inputs improved both models prediction by reducing their complexity and eliminating data collinearity.

TL;DR: A promising technology is the biological capture of CO 2 using microalgae as mentioned in this paper, which has the following advantages: (i) being an environmental sustainable method; (ii) using directly the solar energy; and (iii) co-producing high added value materials based on biomass, such as human food, animal feed, medical drugs, fertilizers, biomolecules for specific applications and biofuels.

TL;DR: In this paper, principal components analysis (PCA) and cluster analysis (CA) were applied to the mass concentrations of sulphur dioxide (SO2) and particulate matter with an aerodynamic diameter less than 10μm collected in the AQMN of Oporto-MA from January 2003 to December 2005.

TL;DR: A pseudo first-order reaction rate with respect to O-II concentration was found to be adequate to fit the data in these experiments, in which kap depends on the initial conditions following a power-law dependency (at optimum pH of 3 and absence of chloride ions).