Cu/Ni‐Loaded CeO2‐ZrO2 Catalyst for the Water‐Gas Shift Reaction: Effects of Loaded Metals and CeO2 Addition

Two different types of metals (Cu and Ni) and the effect of CeO₂ addition to produce a CeO₂‐ZrO₂ co‐supporter were investigated through the water‐gas shift (WGS) reaction. It was found that the WGS activity could be enhanced with CeO₂ addition. At relatively high temperature, Ni‐loaded catalysts exhibited higher CO conversion while Cu‐loaded catalysts demonstrated better performance at low temperatures. The stability and yield of the CO₂ and H₂ products of the Cu catalysts were higher than those of the Ni catalysts. These results may be caused by an irreversible adsorption of CO on Ni and the reverse WGS reaction occurring on the Ni catalysts. In situ diffuse‐reflection infrared Fourier transform spectroscopy data suggests that the WGS mechanism likely proceeded via formate species.     

Optimisation and modelling green bean's ultrasound blanching

Using of ultrasound in food processing is a novel and interesting technique, which is often complementary to classical methods. This study reports on the ultrasound blanching (USB) of green bean. Response surface methodology (RSM) was used to study the effect of process variables on the USB. Three independent variables including temperature (50–90 °C), time (45–225 s) and duty cycle (0.2–0.8 s) were examined. The optimal USB conditions were obtained with a temperature of 90 °C, USB time of 58.27 s and duty cycle of 0.79 s. At these conditions, the residual peroxidase activity (RPA) determined as 9.64% and the vitamin C loss as 8.92%. The experimental values under optimal condition were in good consistent with the predicted values. According to the results, the USB process is more efficient process and as well as less damage to the product compared to the conventional blanching method.     

Green synthesis and characterisation of L-Serine capped magnetite nanoparticles for removal of Rhodamine B from contaminated water

ABSTRACT

This paper describes a green one-pot synthesis of L-Serine (L-Ser) capped magnetite nanoparticles (Fe₃O₄ NPs) and its potential application for adsorption of RhB dye from aqueous solution. The surface property, structure, morphology and magnetic properties of as prepared L-Ser capped Fe₃O₄ NPs were characterised through UV-Visible spectroscopy, Fourier transform-infrared spectroscopy, X-Ray Diffraction (XRD), scanning electron microscope, transmission electron microscope (TEM) and vibrating sample magnetometer (VSM). The XRD results were indicated the formation of high crystalline spinel type Fe₃O₄ NPs. TEM images were shown the spherical shape of L-Ser capped Fe₃O₄ NPs with particle size of 5.9 nm. The VSM curve showed the superparamagnetic behaviour of L-Ser capped Fe₃O₄. A plausible interaction mechanism of L-Ser and Fe₃O₄ NPs was also investigated. L-Ser capped Fe₃O₄ NPs due to its large surface area and a strong magnetism was shown potential adsorption efficiency towards RhB dye from aqueous solution. The adsorption isotherm data fitted well with Langmuir isotherm model and the monolayer adsorption capacity (q_e,exp) was found to be 6.82 mg/g at pH 7.4 and 300 K. The experimental kinetic data fitted very well with the pseudo-second-order model. The thermodynamic studies reveal that adsorption efficiency is critically dependent on temperature.     

On electromagneto-thermoelastic plane waves under Green–Naghdi theory of thermoelasticity-II

The present work attempts to investigate the propagation of one-dimensional electromagneto-thermoelastic plane waves in an isotropic unbounded thermally and electrically conducting media with finite conductivity in the context of the theory of thermoelasticity of Green and Naghdi type-II. The heat conduction equation is affected with the Thomson coe?cient. Basic governing equations are modified by using Green–Naghdi theory of type-II. Our problem formulation derives two different systems. The first system is found to be coupled with the thermal field and represents the longitudinal wave. However, the second system represents transverse wave that is uncoupled with the thermal field. In both the cases, we identify waves that are affected with the magnetic field. Asymptotic expansions of dispersion relation solutions and various components of plane waves such as phase velocity, specific loss, and penetration depth are derived analytically for high- and low-frequency values in all cases. Analytical results predicting the limiting behavior of longitudinal and transverse waves are verified with the numerical results. The results of the present study are compared with the results of the thermoelastic case, and a detailed analysis of the effects of presence of the magnetic field under this theory has been presented.     

Radio planning of energy-aware cellular networks

This paper introduces a joint planning and management optimization approach for cellular networks to limit energy consumption while guaranteeing QoS and minimizing operators Capex and Opex. The modeling framework shows that an effective energy-efficient operation depends on the planning decisions. Conversely, it also shows that planning with energy management operation in view yields more versatile topologies than more traditional models based only on Capex. Results for LTE networks are provided and show that savings up to 65% in energy expenses are possible with slight increases in capital investments.     

Energy policy in the Caribbean green economy context and the Institutional Analysis and Design (IAD) framework as a proposed tool for its development

Market integration efforts of Caribbean small island developing states have become transposed on the growing paradigm shift towards green economy pathways. Central to this is the challenge of implementing Caribbean energy policy in a manner that is aligned with green economy ideals and face the realities of regional indebtedness and environmental impacts. Here we analyze the current state of the Caribbean energy policy development arena and propose that the currently weak policy and institutional design regime might potentially benefit from the application of the Institutional Analysis and Design (IAD) model especially within the operational context of the green economy. It allows us to identify current policy dilemmas, bottlenecks and discrepancies and to disentangle some of them while offering up a way forward with others. We do not so much offer distinct recommendations but focus more on delineating how to clear the pathway for sound policy intervention and outcomes. By doing so we set forth a challenging agenda for future policy analysis research that will advance Caribbean energy policy in more robust ways.     

Data-driven approaches for emissions-minimized paths in urban areas

Concerns about air quality and global warming have led to numerous initiatives to reduce emissions. In general, emissions are proportional to the amount of fuel consumed, and the amount of fuel consumed is a function of speed, distance, acceleration, and weight of the vehicle. In urban areas, vehicles must often travel at the speed of traffic, and congestion can impact this speed particularly at certain times of day. Further, for any given time of day, the observations of speeds on an arc can exhibit significant variability. Because of the nonlinearity of emissions curves, optimizing emissions in an urban area requires explicit consideration of the variability in the speed of traffic on arcs in the network. We introduce a shortest path algorithm that incorporates sampling to both account for variability in travel speeds and to estimate arrival time distributions at nodes on a path. We also suggest a method for transforming speed data into time-dependent emissions values thus converting the problem into a time-dependent, but deterministic shortest path problem. Our results demonstrate the effectiveness of the proposed approaches in reducing emissions relative to the use of minimum distance and time-dependent paths. In this paper, we also identify some of the challenges associated with using large data sets.     

The greenhouse gas abatement potential of enterprise cloud computing

In this paper we present a dynamic, country level methodology and model to determine the energy related Green House Gas (GHG) emissions abatement potential of enterprise cloud computing. The developed model focused upon demonstrating the impact of a move to cloud computing from traditional on-site computing, by creating country specific estimates of energy and GHG reductions. The methodology presented includes variables for market penetration, organisation size, and organisational adoption of on-site and cloud computing. Using the current enterprise cloud service applications of email, customer relationship management (CRM), and groupware against selected global countries, results indicated that 4.5 million tonnes of CO₂e could be reduced with an 80% market penetration for cloud computing. The majority of reductions were calculated to be from small and medium size organisations. A sensitivity analysis of the market penetration and current organisational adoption of cloud computing highlights the possible large variability in overall energy and GHG reductions. An analysis of the model and data used within this study illustrates a requirement for industry and academia to work closely in order to reach the large energy reductions possible with enterprise cloud computing.     

A network approach to overcoming barriers to market engagement for SMEs in energy efficiency initiatives such as the Green Deal

The Green Deal (GD) was launched in 2013 by the UK Government as a market-led scheme to encourage uptake of energy efficiency measures in the UK and create green sector jobs. The scheme closed in July 2015 after 30 months due to government concerns over low uptake and industry standards but additional factors potentially contributed to its failure such as poor scheme design and lack of understanding of the customer and supply chain journey. We explore the role of key delivery agents of GD services, specifically SMEs, and we use the LoCal-Net project as a case study to examine the use of networks to identify and reduce barriers to SME market engagement. We find that SMEs experienced multiple barriers to interaction with the GD such as lack of access to information, training, and confusion over delivery of the scheme but benefited from interaction with the network to access information, improve understanding of the scheme, increasing networking opportunities and forming new business models and partnerships to reduce risk. The importance of SMEs as delivery agents and their role in the design of market-led schemes such as the GD are discussed with recommendations for improving SME engagement in green sector initiatives.