Life cycle assessment of combustion-based electricity generation technologies integrated with carbon capture and storage: A review.

Carbon capture and storage (CCS) is the key technology to reduce CO emissions from the conventional power systems. CCS has the flexibility, compatibility, and great potential to reduce emissions when combined with the current energy infrastructure. Through quantifying the environmental benefits of the combustion-based electricity generation system with CCS by life cycle assessment (LCA), decision-makers can grasp the contribution of upstream and downstream processes to various environmental impacts, a better trade-off between climate change and non-climate impact categories.

Hybrid QSPR models for the prediction of the free energy of solvation of organic solute/solvent pairs.

Due to the importance of the Gibbs free energy of solvation in understanding many physicochemical phenomena, including lipophilicity, phase equilibria and liquid-phase reaction equilibrium and kinetics, there is a need for predictive models that can be applied across large sets of solvents and solutes. In this paper, we propose two quantitative structure property relationships (QSPRs) to predict the Gibbs free energy of solvation, developed using partial least squares (PLS) and multivariate linear regression (MLR) methods for 295 solutes in 210 solvents with total number of data points of 1777. Unlike other QSPR models, the proposed models are not restricted to a specific solvent or solute.

QSPR prediction of the hydroxyl radical rate constant of water contaminants.

In advanced oxidation processes (AOPs), the aqueous hydroxyl radical (HO) acts as a strong oxidant to react with organic contaminants. The hydroxyl radical rate constant (kHO) is important for evaluating and modelling of the AOPs. In this study, quantitative structure-property relationship (QSPR) method is applied to model the hydroxyl radical rate constant for a diverse dataset of 457 water contaminants from 27 various chemical classes.