Understanding mobile phone usage while driving:mini-bus and taxi drivers' experiences in Istanbul

In emerging markets, the amount of mobile communication and the number of occasions mobile phones are used are increasing. More and more settings appropriate or not for mobile phone usage are being exposed. Although prohibited by many governments, there is evidence that use of new mobile devices while driving are somehow becoming current everyday practice, hence legitimatizing usage for many users. Dominant dangerous behavior in the absence of enforced legal framework is being deployed and has become routine for many m-users. This chapter adopts a qualitative case study approach (20 cases) to examine the public transport drivers' motives, logic and legitimacy processes. The question which these issues raise in the light of advancing m-technologies is: How do, in the context of emerging market, undesired emerging routines enactment get to be reflected upon and voluntarily disregarded to maximize the benefits of m-technologies while minimizing their drawbacks? Findings point out at multiple motives for usage including external social pressure through the ubiquitous 24/7 usage of mtechnology, lack of alternative communication protocol, real time need for action and from an internal perspectives boredoms, lack of danger awareness, blurring of the boundaries between personal and business life and lack of job fulfillment are uncovered as key factors. As secondary dynamic factors such as education, drivers work' histories, impunity, lack of strong consumer opposition appear central in shaping the development of the routines. © 2011, IGI Global.

Comparing transport emissions and impacts for energy recovery from domestic waste (EfW): centralised and distributed disposal options for two UK Counties

Many local authorities (LAs) are currently working to reduce both greenhouse gas emissions and the amount of municipal solid waste (MSW) sent to landfill. The recovery of energy from waste (EfW) can assist in meeting both of these objectives. The choice of an EfW policy combines spatial and non-spatial decisions which may be handled using Multi-Criteria Analysis (MCA) and Geographic Information Systems (GIS). This paper addresses the impact of transporting MSW to EfW facilities, analysed as part of a larger decision support system designed to make an overall policy assessment of centralised (large-scale) and distributed (local-scale) approaches. Custom-written ArcMap extensions are used to compare centralised versus distributed approaches, using shortest-path routing based on expected road speed. Results are intersected with 1-kilometre grids and census geographies for meaningful maps of cumulative impact. Case studies are described for two counties in the United Kingdom (UK); Cornwall and Warwickshire. For both case study areas, centralised scenarios generate more traffic, fuel costs and emitted carbon per tonne of MSW processed.

The carbon dioxide emissions of firms:a spatial analysis

In order to gain a greater understanding of firms' 'environmental behaviour' this paper explores the factors that influence firms' emissions intensities and provides the first analysis of the determinants of firm level carbon dioxide (CO2) emissions. Focussing on Japan, the paper also examines whether firms' CO2 emissions are influenced by the emissions of neighbouring firms and other possible sources of spatial correlation. Results suggest that size, the capital-labour ratio, R&D expenditure, the extent of exports and concern for public profile are the key determinants of CO2 emissions. Local lobbying pressure, as captured by regional community characteristics, does not appear to play a role, however emissions are found to be spatially correlated. This raises implications for the manner in which the environmental performance of firms is modelled in future. © 2013 Elsevier Inc.

Investigation into the performance and emissions of a stationary diesel engine fuelled by sewage sludge intermediate pyrolysis oil and biodiesel blends

This paper studies the characteristics of blends of biodiesel and a new type of SSPO (sewage sludge derived intermediate pyrolysis oil) in various ratios, and evaluates the application of such blends in an unmodified Lister diesel engine. The engine performance and exhaust emissions were investigated and compared to those of diesel and biodiesel. The engine injectors were inspected and tested after the experiment. The SSPO-biodiesel blends were found to have comparable heating values to biodiesel, but relatively high acidity and carbon residue. The diesel engine has operated with a 30/70 SSPO-biodiesel blend and a 50/50 blend for up to 10h and there was no apparent deterioration in operation observed. It is concluded that with 30% SSPO, the engine gives better overall performance and fuel consumption than with 50% SSPO. The exhaust temperatures of 30% SSPO and 50% SSPO are similar, but 30% SSPO gives relatively lower NO emission than 50% SSPO. The CO and smoke emissions are lower with 50% SSPO than with 30% SSPO. The injectors of the engine operated with SSPO blends were found to have heavy carbon deposition and noticeably reduced opening pressure, which may lead to deteriorated engine performance and exhaust emissions in extended operation. © 2013 Elsevier Ltd.

Powertrain optimisation in a hybrid electric bus

This paper describes the use of a formal optimisation procedure to optimise a plug-in hybrid electric bus using two different case studies to meet two different performance criteria; minimum journey cost and maximum battery life. The approach is to choose a commercially available vehicle and seek to improve its performance by varying key design parameters. Central to this approach is the ability to develop a representative backward facing model of the vehicle in MATLAB/Simulink along with appropriate optimisation objective and penalty functions. The penalty functions being the margin by which a particular design fails to meet the performance specification. The model is validated against data collected from an actual vehicle and is used to estimate the vehicle performance parameters in a model-in-the-loop process within an optimisation routine. For the purposes of this paper, the journey cost/battery life over a drive cycle is optimised whilst other performance indices are met (or exceeded). Among the available optimisation methods, Powell's method and Simulated Annealing are adopted. The results show this method as a valid alternative modelling approach to vehicle powertrain optimisation. © 2012 IEEE.

Meeting 2050 CO2 emissions reduction targets:The potential for electric vehicles

This chapter explores the potential for electric vehicles to contribute to decarbonising surface transport. Decarbonising transport is a major global challenge-meeting CO2 emissions reduction targets for 2050, with a rapidly growing, and urbanising global population.

Fault diagnosis scheme for open-circuit faults in switched reluctance motor drives using fast Fourier transform algorithm with bus current detection

Reliability of power converters is of crucial importance in switched reluctance motor drives used for safety-critical applications. Open-circuit faults in power converters will cause the motor to run in unbalanced states, and if left untreated, they will lead to damage to the motor and power modules, and even cause a catastrophic failure of the whole drive system. This study is focused on using a single current sensor to detect open-circuit faults accurately. An asymmetrical half-bridge converter is considered in this study and the faults of single-phase open and two-phase open are analysed. Three different bus positions are defined. On the basis of a fast Fourier transform algorithm with Blackman window interpolation, the bus current spectrums before and after open-circuit faults are analysed in details. Their fault characteristics are extracted accurately by the normalisations of the phase fundamental frequency component and double phase fundamental frequency component, and the fault characteristics of the three bus detection schemes are also compared. The open-circuit faults can be located by finding the relationship between the bus current and rotor position. The effectiveness of the proposed diagnosis method is validated by the simulation results and experimental tests.

CO2 emissions reduction of Chinese light manufacturing industries:a novel RAM-based global Malmquist-Luenberger productivity index

Climate change has become one of the most challenging issues facing the world. Chinese government has realized the importance of energy conservation and prevention of the climate changes for sustainable development of China's economy and set targets for CO2 emissions reduction in China. In China industry contributes 84.2% of the total CO2 emissions, especially manufacturing industries. Data envelopment analysis (DEA) and Malmquist productivity (MP) index are the widely used mathematical techniques to address the relative efficiency and productivity of a group of homogenous decision making units, e.g. industries or countries. However, in many real applications, especially those related to energy efficiency, there are often undesirable outputs, e.g. the pollutions, waste and CO2 emissions, which are produced inevitably with desirable outputs in the production. This paper introduces a novel Malmquist-Luenberger productivity (MLP) index based on directional distance function (DDF) to address the issue of productivity evolution of DMUs in the presence of undesirable outputs. The new RAM (Range-adjusted measure)-based global MLP index has been applied to evaluate CO2 emissions reduction in Chinese light manufacturing industries. Recommendations for policy makers have been discussed.

A framework for measuring global Malmquist–Luenberger productivity index with CO2 emissions on Chinese manufacturing industries

China has achieved significant progress in terms of economic and social developments since implementation of reform and open policy in 1978. However, the rapid speed of economic growth in China has also resulted in high energy consumption and serious environmental problems, which hindering the sustainability of China's economic growth. This paper provides a framework for measuring eco-efficiency with CO2 emissions in Chinese manufacturing industries. We introduce a global Malmquist-Luenberger productivity index (GMLPI) that can handle undesirable factors within Data Envelopment Analysis (DEA). This study suggested after regulations imposed by the Chinese government, in the last stage of the analysis, i.e. during 2011–2012, the contemporaneous frontier shifts towards the global technology frontier in the direction of more desirable outputs and less undesirable outputs, i.e. producing less CO2 emissions, but the GMLPI drops slightly. This is an indication that the Chinese government needs to implement more policy regulations in order to maintain productivity index while reducing CO2 emissions.