Opportunities to reduce Greenhouse Gas Emissions in the Urban Passenger Transport Sector

This paper sets out to appraise the body of literature which has investigated the potential role of a large number of strategies designed to reduce greenhouse gas emissions, in line with the objectives set under the Rio Convention. The paper discusses the role of (i) technological vs behavioural ‘fixes’, (ii) the changing spatial and temporal dimension of work activity, (iii) the jobshousing balance and land use, (iv) conventional and alternative fuels, and (v) pricing, charges and taxes. This review and assessment is part of an ongoing study funded by the Bureau of Transport and Communication Economics investigating the cost effectiveness of alternative ways of reducing greenhouse gas emissions in urban areas in Australia. We draw on a number of real experiments to illustrate the types of policies which are likely to have the greatest impact, given the cost implications

Consumer-Based Carbon Reduction Incentives: A Proposed Mixed Incentive Scheme for Reducing Co2 Emissions From Transport

To be cost effective the abatement greenhouse gases should be spread across the spectrum of emission sources. While energy production generates the largest share of greenhouse gases, emissions produced by vehicular transport in Australia is still a significant contributor and should bear at least some burden of abatement. Approaches to reducing greenhouse gases have tended thus far to focus on industry. In the transport sector, this industry-based approach has focussed on emission standards. But to be truly cost effective, incentives to reduce emissions need to be targeted at the point of use, by both industry and the private individuals. This paper explores the benefits and limitations of adopting a mixed incentive scheme applied to fuel consumers to reduce greenhouse gas emissions from transport. The proposed consumer-based carbon reduction incentive scheme (CBCRI) incorporates elements of tradeable permits, carbon taxes and emission reduction subsidies.</p

Road Networks Management under Uncertainty: A stochastic based model

Current pavement management systems (PMS) adopted by the Road Authorities are often very complex and data intensive. Other challenges also faced by Road Authorities in managing road networks include budget constraints and the uncertainty associated in predicting the future performance of pavements. In addition, the emphasis in pavement management has shifted from reconstructing completely new roads towards preservation of existing networks. In many cases, existing PMS do not meet these requirements. Thus, an efficient model that is able to accommodate all of those challenges needs to be developed. This paper outlines the development of a stochastic based PMS that includes a performance prediction model using Markov chains and an optimization model based on Markov Decision Processes (MDP). Combinations of pavement preservation strategies and maintenance budget levels are applied as action criteria in contrast to other stochastic models. Despite the apparent influence of uncertainty in road pavement performance during their service live, stochastic models provide promising results for enhancing current PMS. By analysing historical data, the future behaviour of road pavements under different expenditure levels and combination of routine and periodic maintenance measures can be predicted. From an optimization point of view, the utilization of constrained MDP will potentially result in cost savings. This is due to the optimality principal of the model which is capable of finding a optimal multi-year maintenance policy through the direct inclusion of additional constraints into the optimization problem. Hence, the model considers constraints and incorporates relationships between historical maintenance actions and costs. This paper also presents a methodology for developing rationale for long-term maintenance policies by integrating stochastic based performance prediction and optimization models with the experience of Road Authorities in managing roads networks

Residential broadband subscription demand: an econometric analysis of Australian choice experiment data

The recent roll-out of fibre-optic cable suggests that the willingness of households in passed communities to subscribe to networked services is an important issue. This paper studies the determination of the demand for network subscription. Through a discrete choice model the effect of installation and rental price on the likelihood of subscription is analysed. The logit regression is based on choice experiment (stated preference) subscription data obtained from a national survey of households. Limitations of this preliminary work and suggestions for future research are discussed.