A methodology to measure the environmental impact of ICT operating systems across different device platforms

Abstract: A new methodology was created to measure the energy consumption and related green house gas (GHG) emissions of a computer operating system (OS) across different device platforms. The methodology involved the direct power measurement of devices under different activity states. In order to include all aspects of an OS, the methodology included measurements in various OS modes, whilst uniquely, also incorporating measurements when running an array of defined software activities, so as to include OS application management features. The methodology was demonstrated on a laptop and phone that could each run multiple OSs, results confirmed that OS can significantly impact the energy consumption of devices. In particular, the new versions of the Microsoft Windows OS were tested and highlighted significant differences between the OS versions on the same hardware. The developed methodology could enable a greater awareness of energy consumption, during both the software development and software marketing processes.

Modelling personal thermal sensations using C-Support Vector Classification (C-SVC) algorithm

The personalised conditioning system (PCS) is widely studied. Potentially, it is able to reduce energy consumption while securing occupants’ thermal comfort requirements. It has been suggested that automatic optimised operation schemes for PCS should be introduced to avoid energy wastage and discomfort caused by inappropriate operation. In certain automatic operation schemes, personalised thermal sensation models are applied as key components to help in setting targets for PCS operation. In this research, a novel personal thermal sensation modelling method based on the C-Support Vector Classification (C-SVC) algorithm has been developed for PCS control. The personal thermal sensation modelling has been regarded as a classification problem. During the modelling process, the method ‘learns’ an occupant’s thermal preferences from his/her feedback, environmental parameters and personal physiological and behavioural factors. The modelling method has been verified by comparing the actual thermal sensation vote (TSV) with the modelled one based on 20 individual cases. Furthermore, the accuracy of each individual thermal sensation model has been compared with the outcomes of the PMV model. The results indicate that the modelling method presented in this paper is an effective tool to model personal thermal sensations and could be integrated within the PCS for optimised system operation and control.

Bio-inspired ant colony optimization based clustering algorithm with mobile sinks for applications in consumer home automation networks

With the fast development of wireless communications, ZigBee and semiconductor devices, home automation networks have recently become very popular. Since typical consumer products deployed in home automation networks are often powered by tiny and limited batteries, one of the most challenging research issues is concerning energy reduction and the balancing of energy consumption across the network in order to prolong the home network lifetime for consumer devices. The introduction of clustering and sink mobility techniques into home automation networks have been shown to be an efficient way to improve the network performance and have received significant research attention. Taking inspiration from nature, this paper proposes an Ant Colony Optimization (ACO) based clustering algorithm specifically with mobile sink support for home automation networks. In this work, the network is divided into several clusters and cluster heads are selected within each cluster. Then, a mobile sink communicates with each cluster head to collect data directly through short range communications. The ACO algorithm has been utilized in this work in order to find the optimal mobility trajectory for the mobile sink. Extensive simulation results from this research show that the proposed algorithm significantly improves home network performance when using mobile sinks in terms of energy consumption and network lifetime as compared to other routing algorithms currently deployed for home automation networks.

Thermal and visual performance of real and theoretical thermochromic glazing solutions for office buildings

Thermochromic windows are able to modulate their transmittance in both the visible and the near-infrared field as a function of their temperature. As a consequence, they allow to control the solar gains in summer, thus reducing the energy needs for space cooling. However, they may also yield a reduction in the daylight availability, which results in the energy consumption for indoor artificial lighting being increased. This paper investigates, by means of dynamic simulations, the application of thermochromic windows to an existing office building in terms of energy savings on an annual basis, while also focusing on the effects in terms of daylighting and thermal comfort. In particular, due attention is paid to daylight availability, described through illuminance maps and by the calculation of the daylight factor, which in several countries is subject thresholds. The study considers both a commercially available thermochromic pane and a series of theoretical thermochromic glazing. The expected performance is compared to static clear and reflective insulating glass units. The simulations are repeated in different climatic conditions, showing that the overall energy savings compared to clear glazing can range from around 5% for cold climates to around 20% in warm climates, while not compromising daylight availability. Moreover the role played by the transition temperature of the pane is examined, pointing out an optimal transition temperatures that is irrespective of the climatic conditions.

Assessing how retrofit of traditional buildings impacts indoor environment and occupant’s thermal comfort

Buildings consume a large amount of energy, in both their use and production. Retrofitting aims to achieve a reduction in this energy consumption. However, there are concerns that retrofitting can cause negative impacts on the internal environment including poor thermal comfort and health issues. This research investigates the impact of retrofitting the façade of existing traditional buildings and the resulting impact on the indoor environment and occupant thermal comfort. A Case building located at the University of Reading has been monitored experimentally and modelled using IES software with monitored values as input conditions for the model. The proposed façade related retrofit options have been simulated and provide information on their effect on the indoor environment. The findings show a positive impact on the internal environment. The data shows a 16.2% improvement in thermal comfort after retrofit is simulated. This also achieved a 21.6% reduction in energy consumption from the existing building.

Decolourisation of real textile waste using electrochemical techniques: Effect of electrode composition

The present paper presents the study of the decolourisation of real textile effluent by constant current electrolysis in a flow-cell using a DSAO type material. The effect of using different anode materials (Ti/Ru0.3Ti0.7O2; Ti/Ir0.3Ti0.7O2; Ti/RuxSn1-xO2, where X = 0.1, 0.2 or 0.3) on the efficiency of colour removal is discussed. Attempts to perform galvanostatic oxidation (40 and 60 mA cm(-2)) on the as-received effluent demonstrate that colour removal and total organic carbon (TOC) removal are limited. In this case the greatest degree of colour removal is achieved when anode containing 90% SnO2 is used. If the conductivity of the effluent is increased by adding NaCl (0.1 mol L-1) appreciable colour/TOC removal is observed. The efficiencies of colour and TOC removal are discussed in terms of the energy per order (E-EO/kWhm(-3) order(-1)) and energy consumption (E-C/kW h kg(-1) TOC), respectively. Finally, the extent of colour removal is compared to consent levels presented in the literature. (C) 2008 Elsevier B.V. All rights reserved.

Pineapple Leaf Fibers for Composites and Cellulose

Pineapple leaf fiber (PALF) which is rich in cellulose, abundantly available, relatively inexpensive, low density, nonabrasive nature, high filling level possible, low energy consumption, high specific properties, biodegradability and has the potential for polymer reinforcement. The utilization of pineapple leaf fiber (PALF) as reinforcements in thermoplastic and thermosetting resins in micro and nano form for developing low cost and lightweight composites is an emerging field of research in polymer science and technology. In this paper we examines the industrial applicabiliy of PALF, mainly for production of composite materials and special papers, chemical feedstocks (bromelin enzyme) and fabrics.