Analysis of solar energy development strategies for a successful energy transition in the UAE

© 2022 The Authors. Published by MDPI AG. This is an open access article available under a Creative Commons licence. The published version can be accessed at the following link on the publisher’s website: https://www.mdpi.com/2227-9717/10/7/1338The United Arab Emirates (UAE) is making significant progress in improving its economy by attracting tourists and trade. In the short run, however, economic activity will continue to be more based on oil, natural gas, and related industries. Rising demand for natural gas for power plants and industrial users, such as petrochemicals and steelmakers, has made the UAE a net gas importer, prompting the country to launch multibillion-dollar investments in nuclear and renewable energy. This study addresses the trend of solar energy production and consumption in the UAE. The strengths, weaknesses, opportunities, and threats (SWOT) analysis was performed on the different types of solar energy in the UAE, and some strategies were developed based on it. The SWOT analysis reveals promising strategies for the UAE’s solar energy transition that would reduce fossil fuel demand, mitigate greenhouse gas emissions through solar energy production, and transform the UAE into the carbon market centre of the Gulf Cooperation Council countries.This research received no external funding.Published onlin

Environmental aspects of the combined cooling, heating, and power (CCHP) systems: a review

© 2022 The Authors. Published by MDPI AG. This is an open access article available under a Creative Commons licence. The published version can be accessed at the following link on the publisher’s website: https://doi.org/10.3390/pr10040711Expanding cities means increasing the need for energy in the residential sector. The supply of this energy must be in environmentally friendly ways; one method of meeting demand in the residential sector is the use of combined cooling, heating, and power (CCHP) systems. The current review paper shows that due to the high cost of gas and electricity, CCHP can be used in various sectors, such as hospitals and airports, to reduce energy consumption with lower environmental impacts by using renewable energy systems as the main driver. While CCHP systems are not feasible in tropical regions with high cooling demand, a solar hybrid system is a superior candidate for regions with sufficient radiation. CCHP can also be used in sectors such as wastewater treatment units, desalination systems, and hydrogen production units to improve performance and increase productivity. The carbon and water footprints of CCHP systems are discussed in detail. The main drivers for reducing carbon and water footprints are improving system components such as the combustion engine and increasing productivity by expanding the system to multi-generation systems. Finally, the carbon tax index can help reduce carbon emissions if properly used in the right context. Based on our best knowledge, there is no extensive review of the environmental aspects of CCHP systems in the literature.Published versio

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

© 2019 The Authors. Published by the Royal Society of Chemistry. This is an open access article available under a Creative Commons licence. The published version can be accessed at the following link on the publisher’s website: https://doi.org/10.1039/C8CP07562JDue 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. Furthermore, while most QSPR models include either experimental or quantum mechanical descriptors, the proposed models combine both, using experimental descriptors to represent the solvent and quantum mechanical descriptors to represent the solute. Up to twelve experimental descriptors and nine quantum mechanical descriptors are considered in the proposed models. Extensive internal and external validation is undertaken to assess model accuracy in predicting the Gibbs free energy of solvation for a large number of solute/solvent pairs. The best MLR model, which includes three solute descriptors and two solvent properties, yields a coefficient of determination (R2) of 0.88 and a root mean squared error (RMSE) of 0.59 kcal mol−1 for the training set. The best PLS model includes six latent variables, and has an R2 value of 0.91 and a RMSE of 0.52 kcal mol−1. The proposed models are compared to selected results based on continuum solvation quantum chemistry calculations. They enable the fast prediction of the Gibbs free energy of solvation of a wide range of solutes in different solvents.Financial support from Eli Lilly via the Lilly Research Award Program (LRAP) and from the UK Engineering and Physical Sciences Research Council (EPSRC) of the UK via a Leadership Fellowship (EP/J003840/1) is gratefully acknowledged.Published onlin

Process modelling, validation and analysis of rotating packed bed stripper in the context of intensified CO2 capture with MEA

Rotating packed bed (RPB) system has applications in CO2 removal using chemical solvents which can reduce the size about ten times compared to common packed bed (PB) system. In this study, RPB stripper using monoethanolamine (MEA) solution is modelled in gPROMS® software. The model has been validated using experimental data from literature and show good agreement. In addition to stripper modelling and validation, the process analysis is accomplished in this study by assessing the influence of four parameters namely rotor speed, reboiler temperature, flow rate of rich liquid, and pressure on desorption efficiency and desorption energy

Modeling of carbon dioxide absorption by solution of piperazine and methyldiethanolamine in a rotating packed bed

This is an accepted manuscript of an article published by Elsevier in Chemical Engineering Science on 15/09/2021, available online: https://doi.org/10.1016/j.ces.2021.117118 The accepted version of the publication may differ from the final published version.CO2 removal by the blended amine solution of piperazine (PZ) and methyldiethanolamine (MDEA) with the various molar concentration ratios in a rotating packed bed (RPB) was modelled using MATLAB linked to Aspen Plus. All the required correlations for the RPB in addition to the mass and energy balances were written in MATLAB while the demanded physical and transport properties were extracted from Aspen Plus. The similar operating conditions and compositions in the reported experiments were used to run the model by the two-film theory for mass transfer as steady state, while the impact of five different parameters on the CO2 absorption efficiency was examined to validate the model. The modeling results are in good agreement with the experimental data for which the average absolute deviation is less than 7.0%. The process analysis revealed that rotational speed and PZ concentration have the most significant effects on CO2 absorption efficiency.This work was financially supported by the National Natural Science Foundation of China (No. 22078009).Published versio

Optical fiber sensor based on magneto-plasmonic features of Ag-Co nanostructure for ppm ammonium detection in aqueous solutions

This is an accepted manuscript of an article published by Elsevier in Optical Fiber Technology on 03/11/2021, available online: https://doi.org/10.1016/j.yofte.2021.102730 The accepted version of the publication may differ from the final published version.Magneto-plasmonic nanocomposite deposition enables fiber optic sensors to detect water pollution caused by chemical contaminants of ammonium that is harmful to human and aquatic organisms as well. In this study, Ag-Co nanocomposite was deposited on unclad multimode glass fiber to distinguish the ammonium concentration in the aqueous medium. Prior to the fabrication of the fiber probe, for finding the stronger surface plasmon resonance (SPR) effect, Ag-Co nanocomposite (which had different structures) was deposited on the glass prism. The maximum SPR shift of 7.16° was observed by varying the ammonium concentration from 0 to 80 ppm, when Ag was deposited as the outer layer and Co acted as the inner layer. The working principle of the sensor was based on manipulating the analyte viscosity with the magnetization of Co nanolayer exposed to the external magnetic field and adjusting the SPR conditions via the interaction of different ammonium concentrations with the Ag layer. Spectral wavelength and the intensity interrogation technique in the visible region confirmed the detection of ammonium in the solution with sensitivity, response time, limit of detection (LOD), and recovery time of 0.131 nm/ppm, 17 s, 2.9 ppm, and 12 s, respectively. These features together with a high selectivity make the proposed sensor a potential candidate for determining the environmental pollution, controlling the industrial safety requirements, and accurately measuring the water quality in daily life.Published versio