School children’s personal exposure to ultrafine particles in the urban environment

There has been considerable scientific interest in personal exposure to ultrafine particles (UFP). In this study, the inhaled particle surface area doses and dose relative intensities in the tracheobronchial and alveolar regions of lungs were calculated using the measured 24-hour UFP time series of school children personal exposures for each recorded activity. Bayesian hierarchical modelling was used to determine mean doses and dose intensities for the various microenvironments. Analysis of measured personal exposures for 137 participating children from 25 schools in the Brisbane Metropolitan Area showed similar trends for all the participating children. Bayesian regression modelling was performed to calculate the daily proportion of children's total doses at different microenvironments. The proportion of alveolar doses in the total daily dose for \emph{home}, \emph{school}, \emph{commuting} and \emph{other} were 55.3\%, 35.3\%, 4.5\% and 5.0\%, respectively, with the \emph{home} microenvironment contributing a majority of children's total daily dose. Children's mean indoor dose was never higher than the outdoor's at any of the schools, indicating there were no persistent indoor particle sources in the classrooms during the measurements. Outdoor activities, eating/cooking at home and commuting were the three activities with the highest dose intensities. Personal exposure was more influenced by the ambient particle levels than immediate traffic.

An examination of the legislative framework governing commuter safety in the Queensland Mining Industry

Commuting in the mining industry -Background -The problem -Journey management -The structure of the legislative framework Legislation and Regulation -Workplace safety in Queensland mining -Risk management -Mining legislation and journey management -Commuting and employee responsibilities -Queensland Workers’ Compensation Scheme Industry standards -Industry standards and journey management Regulated and organisational policy documents -Policy documents and journey management Observations & Conclusions

Bike share's impact on car use : evidence from the United States, Great Britain, and Australia

There are currently more than 400 cities operating bike share programs. Purported benefits of bike share programs include flexible mobility, physical activity, reduced congestion, emissions and fuel use. Implicit or explicit in the calculation of program benefits are assumptions regarding the modes of travel replaced by bike share journeys. This paper examines the degree to which car trips are replaced by bike share, through an examination of survey and trip data from bike share programs in Melbourne, Brisbane, Washing, D.C., London, and Minneapolis/St. Paul. A secondary and unique component of this analysis examines motor vehicle support services required for bike share fleet rebalancing and maintenance. These two components are then combined to estimate bike share’s overall contribution to changes in vehicle kilometres traveled. The results indicate that the estimated mean reduction in car use due to bike share is at least twice the distance covered by operator support vehicles, with the exception of London, in which the relationship is reversed, largely due to a low car mode substitution rate. As bike share programs mature, evaluation of their effectiveness in reducing car use may become increasingly important. This paper reveals that by increasing the convenience of bike share relative to car use and by improving perceptions of safety, the capacity of bike share programs to reduce vehicle trips and yield overall net benefits will be enhanced. Researchers can adapt the analytical approach proposed in this paper to assist in the evaluation of current and future bike share programs.

The impact of a congestion charging exemption on the demand for new low‐emission vehicles

Numerous initiatives have been employed around the world in order to address rising greenhouse gas (GHG) emissions originating from the transport sector. These measures include: travel demand management (congestion‐charging), increased fuel taxes, alternative fuel subsidies and low‐emission vehicle (LEV) rebates. Incentivizing the purchase of LEVs has been one of the more prevalent approaches in attempting to tackle this global issue. LEVs, whilst having the advantage of lower emissions and, in some cases, more efficient fuel consumption, also bring the downsides of increased purchase cost, reduced convenience of vehicle fuelling, and operational uncertainty. To stimulate demand in the face of these challenges, various incentive‐based policies, such as toll exemptions, have been used by national and local governments to encourage the purchase of these types of vehicles. In order to address rising GHG emissions in Stockholm, and in line with the Swedish Government’s ambition to operate a fossil free fleet by 2030, a number of policies were implemented targeting the transport sector. Foremost amongst these was the combination of a congestion charge – initiated to discourage emissions‐intensive travel – and an exemption from this charge for some LEVs, established to encourage a transition towards a ‘green’ vehicle fleet. Although both policies shared the aim of reducing GHG emissions, the exemption for LEVs carried the risk of diminishing the effectiveness of the congestion charging scheme. As the number of vehicle owners choosing to transition to an eligible LEV increased, the congestion‐reduction effectiveness of the charging scheme weakened. In fact, policy makers quickly recognized this potential issue and consequently phased out the LEV exemption less than 18 months after its introduction (1). Several studies have investigated the demand for LEVs through stated‐preference (SP) surveys across multiple countries, including: Denmark (2), Germany (3, 4), UK (5), Canada (6), USA (7, 8) and Australia (9). Although each of these studies differed in approach, all involved SP surveys where differing characteristics between various types of vehicles, including LEVs, were presented to respondents and these respondents in turn made hypothetical decisions about which vehicle they would be most likely to purchase. Although these studies revealed a number of interesting findings in regards to the potential demand for LEVs, they relied on SP data. In contrast, this paper employs an approach where LEV choice is modelled by taking a retrospective view and by using revealed preference (RP) data. By examining the revealed preferences of vehicle owners in Stockholm, this study overcomes one of the principal limitations of SP data, namely that stated preferences may not in fact reflect individuals’ actual choices, such as when cost, time, and inconvenience factors are real rather than hypothetical. This paper’s RP approach involves modelling the characteristics of individuals who purchased new LEVs, whilst estimating the effect of the congestion charging exemption upon choice probabilities and subsequent aggregate demand. The paper contributes to the current literature by examining the effectiveness of a toll exemption under revealed preference conditions, and by assessing the total effect of the policy based on key indicators for policy makers, including: vehicle owner home location, commuting patterns, number of children, age, gender and income. Extended Abstract Submission for Kuhmo Nectar Conference 2014 2 The two main research questions motivating this study were:  Which individuals chose to purchase a new LEV in Stockholm in 2008?; and,  How did the congestion charging exemption affect the aggregate demand for new LEVs in Stockholm in 2008? In order to answer these research questions the analysis was split into two stages. Firstly, a multinomial logit (MNL) model was used to identify which demographic characteristics were most significantly related to the purchase of an LEV over a conventional vehicle. The three most significant variables were found to be: intra‐cordon residency (positive); commuting across the cordon (positive); and distance of residence from the cordon (negative). In order to estimate the effect of the exemption policy on vehicle purchase choice, the model included variables to control for geographic differences in preferences, based on the location of the vehicle owners’ homes and workplaces in relation to the congestion‐charging cordon boundary. These variables included one indicator representing commutes across the cordon and another indicator representing intra‐cordon residency. The effect of the exemption policy on the probability of purchasing LEVs was estimated in the second stage of the analysis by focusing on the groups of vehicle owners that were most likely to have been affected by the policy i.e. those commuting across the cordon boundary (in both directions). Given the inclusion of the indicator variable representing commutes across the cordon, it is assumed that the estimated coefficient of this variable captures the effect of the exemption policy on the utility of choosing to purchase an exempt LEV for these two groups of vehicle owners. The intra‐cordon residency indicator variable also controls for differences between the two groups, based upon direction of travel across the cordon boundary. A counter‐hypothesis to this assumption is that the coefficient of the variable representing commuting across the cordon boundary instead only captures geo‐demographic differences that lead to variations in LEV ownership across the different groups of vehicle owners in relation to the cordon boundary. In order to address this counter‐hypothesis, an additional analysis was performed on data from a city with a similar geodemographic pattern to Stockholm, Gothenburg ‐ Sweden’s second largest city. The results of this analysis provided evidence to support the argument that the coefficient of the variable representing commutes across the cordon was capturing the effect of the exemption policy. Based upon this framework, the predicted vehicle type shares were calculated using the estimated coefficients of the MNL model and compared with predicted vehicle type shares from a simulated scenario where the exemption policy was inactive. This simulated scenario was constructed by setting the coefficient for the variable representing commutes across the cordon boundary to zero for all observations to remove the utility benefit of the exemption policy. Overall, the procedure of this second stage of the analysis led to results showing that the exemption had a substantial effect upon the probability of purchasing and aggregate demand for exempt LEVs in Stockholm during 2008. By making use of unique evidence of revealed preferences of LEV owners, this study identifies the common characteristics of new LEV owners and estimates the effect of Stockholm's congestion charging exemption upon the demand for new LEVs during 2008. It was found that the variables that had the greatest effect upon the choice of purchasing an exempt LEV included intra‐cordon residency (positive), distance of home from the cordon (negative), and commuting across the cordon (positive). It was also determined that owners under the age of 30 years preferred non‐exempt LEVs (low CO2 LEVs), whilst those over the age of 30 years preferred electric vehicles. In terms of electric vehicles, it was apparent that those individuals living within the city had the highest propensity towards purchasing this vehicle type. A negative relationship between choosing an electric vehicle and the distance of an individuals’ residency from the cordon was also evident. Overall, the congestion charging exemption was found to have increased the share of exempt LEVs in Stockholm by 1.9%, with, as expected, a much stronger effect on those commuting across the boundary, with those living inside the cordon having a 13.1% increase, and those owners living outside the cordon having a 5.0% increase. This increase in demand corresponded to an additional 538 (+/‐ 93; 95% C.I.) new exempt LEVs purchased in Stockholm during 2008 (out of a total of 5 427; 9.9%). Policy makers can take note that an incentive‐based policy can increase the demand for LEVs and appears to be an appropriate approach to adopt when attempting to reduce transport emissions through encouraging a transition towards a ‘green’ vehicle fleet.

Bike share's impact on car use : evidence from the United States, Great Britain, and Australia

There are currently more than 700 cities operating bike share programs. Purported benefits of bike share include flexible mobility, physical activity, reduced congestion, emissions and fuel use. Implicit or explicit in the calculation of program benefits are assumptions regarding the modes of travel replaced by bike share journeys. This paper examines the degree to which car trips are replaced by bike share, through an examination of survey and trip data from bike share programs in Melbourne, Brisbane, Washington, D.C., London, and Minneapolis/St. Paul. A secondary and unique component of this analysis examines motor vehicle support services required for bike share fleet rebalancing and maintenance. These two components are then combined to estimate bike share’s overall contribution to changes in vehicle kilometers traveled. The results indicate an estimated reduction in motor vehicle use due to bike share of approx. 90,000 km per annum in Melbourne and Minneapolis/St. Paul and 243,291 km for Washington, D.C. London’s bike share program however recorded an additional 766,341 km in motor vehicle use. This was largely due to a low car mode substitution rate and substantial truck use for rebalancing of bicycles. As bike share programs mature, evaluation of their effectiveness in reducing car use may become increasingly important. Researchers can adapt the analytical approach proposed in this paper to assist in the evaluation of current and future bike share programs.

Industry in Jarrow

This study was done during 1958-59 as part of a geography major at London Institute of Education, Eastbourne Teachers' Training College, Sussex 1957-59. (Age 19) I visited all factories, industries and wharfs on my bicycle and interviewed managers, owners and supervisors.

Control of solar powered micro-grids using electric vehicles

Large scale solar plants are gaining recognition as potential energy sources for future. In this paper, the feasibility of using electric vehicles (EVs) to control a solar powered micro-grid is investigated in detail. The paper presents a PSCAD/EMTDC based model for the solar powered micro-grid with EVs. EVs are expected to have both the vehicle-to-grid (V2G) and grid-to-vehicle (G2V) capability, through which energy can either be injected into or extracted from the solar powered micro-grid to control its energy imbalance. Using the model, the behaviour of the micro-grid is investigated under a given load profile, and the results indicate that a minimum number of EVs are required to meet the energy imbalance and it is time dependent and influenced by various factors such as depth of charge, commuting profiles, reliability etc...

A comparison of factors influencing perceived risk by French and Australian cyclists and drivers

Differences in the levels of risk perceived by cyclists and car drivers may contribute to the dangers in their interactions. Levels of perceived risk have been shown to vary according to personal and environmental factors and between countries. Cycling rates in France are higher than in Australia, particularly among women. This study investigated whether cultural differences between France and Australia are reflected in perceived risks for experienced adult cyclists and drivers in the two countries. In online surveys, regular cyclists (France 336, Australia 444) and drivers (France 92, Australia 151) were asked to rate the level of risk in six situations: failure to yield; going through a red light; not signalling when turning; swerving; tail-gating; and not checking traffic. The effects of type of interacting vehicle and participant type on perceived risk were similar in France and Australia. However, the influence of responsibility for the risky behaviour differed according to participant type, type of situation and nationality. When the bicycle rider committed the road rule violation, Australian cyclists and drivers gave higher risk ratings than French cyclists and drivers. In both countries, cyclists rated themselves significantly higher than drivers on the perceived control and overconfidence subscales of the perceived skill measure. The French cyclists rated themselves higher than Australian cyclists on these scales, which could be responsible for overall lower perceived risk levels when interacting with a bike. Australian cyclists rated themselves significantly lower than drivers on the incompetence subscale but French cyclists rated themselves higher than drivers. In both countries incompetence scores were positively related to levels of perceived risk. Weekly time was associated with perceived risk in Australia but not in France. Frequency of traffic violations was not associated with perceived risk in either country. In conclusion, levels of perceived risk differed between drivers and cyclists in both countries and were influenced by type of interacting vehicle, experience and perceived skill. However, some differences between the results from the two countries merit further investigation to shed light on potential improvements in safety and cycling participation.

Mobility in the child (and carer) friendly city : SEQ vs. Stockholm

The rationale for providing state subsidised public transport has changed over time from a social obligation to provide transport options for those without access to private transport to an environmental and economic imperative to minimize congestion and greenhouse gas emissions. In many jurisdictions this shift has seen a greater focus on the provision of peak hour commuter services and a shift in the demographic profile of the riding public and a significant increase in the number of commuter passengers relative to others. The scheduling of commuter services is not geared to meet the needs of children and their generally female carers who often need to engage in trip chaining and travel outside peak commuting periods and on weekends. In addition to service scheduling difficulties, transport infrastructure, both on-board and supporting infrastructure such as bus stops, train stations and connecting footpaths often do not support children and their carers to use public transport services. Combined with a negative attitude by passengers and service providers, such as bus drivers, which may see children, babies and young people as out of place and unwelcome on commuter services, these issues conspire to hinder the use of public transport by children and their carers. Overlaying feminist geography analysis and insights and child-friendly cities objectives, this paper proposes some basic criteria for the provision of public transport services and supporting infrastructure which meets the needs of children, babies and their carers and juxtaposes the achievement of these in South East Queensland, Australia and Stockholm, Sweden.

From stadium to page : why football deserves more fiction

A great football novel is like a perfectly executed bicycle-kick goal, like players such as Argentine legends Diego Maradona and Lionel Messi; they come along once in a generation. Against the accumulated volume of non-fiction football literature (some people still call it soccer), which could fill and spill out of a World Cup Stadium, football novels are comparatively rare. That said, football or soccer fiction is a genre with a very real and important historical longevity...

Barriers to bikesharing : an analysis from Melbourne and Brisbane

This study quantifies the motivators and barriers to bikeshare program usage in Australia. An online survey was administered to a sample of annual members of Australia’s two bikeshare programs based in Brisbane and Melbourne, to assess motivations for joining the schemes. Non-members of the programs were also sampled in order to identify current barriers to joining bikeshare. Spatial analysis from Brisbane revealed residential and work locations of non-members were more geographically dispersed than for bikeshare members. An analysis of bikeshare usage in Melbourne showed a strong relationship between docking stations in areas with relatively less accessible public transit opportunities. The most influential barriers to bikeshare use related to motorized travel being too convenient and docking stations not being sufficiently close to home, work and other frequented destinations. The findings suggest that bikeshare programs may attract increased membership by ensuring travel times are competitive with motorized travel, for example through efficient bicycle routing and priority progression and, by expanding docking station locations, and by increasing the level of convenience associated with scheme use. Convenience considerations may include strategic location of docking stations, ease of signing up and integration with public transport.

Boosting the effects of a curriculum based injury prevention program through a school connectedness intervention : final report to NRMA-ACT Road Safety Trust

Injury is the leading cause of death among young people (AIHW, 2008). A primary contributing factor to injury among adolescents is risk taking behaviour, including road related risks such as risky bicycle and motorcycle use and riding with dangerous or drink-drivers. Injury rates increase dramatically throughout adolescence, at the same time as adolescents are becoming more involved in risk taking behaviour. Also throughout this period, adolescents‟ connectedness to school is decreasing (Monahan, Oesterle & Hawkins, 2010; Whitlock, 2004). School connectedness refers to „the extent to which students feel personally accepted, respected, included, and supported by others in the school‟ (Goodenow, 1993, p. 80), and has been repeatedly shown to be a critical protective factor in adolescent development. For example, school connectedness has been shown to be associated with decreased risk taking behaviour, including violence and alcohol and other drug use (e.g., Resnick et al., 1997), as well as with decreased transport risk taking and vehicle related injuries (Chapman et al., accepted April 2011). This project involved the pilot evaluation of a school connectedness intervention (a professional development program for teachers) to reduce adolescent risk taking behaviour and injury. This intervention has been developed for use as a component of the Skills for Preventing Injury in Youth (SPIY) curriculum based injury prevention program for early adolescents. The objectives of this research were to: 1. Implement a trial School Connectedness intervention (professional development program for teachers) in ACT high schools, and evaluate using comparison high schools. 2. Determine whether the School Connectedness program impacts on adolescent risk taking behaviour and associated injuries (particularly transport risks and injuries). 3. Evaluate the process effectiveness of the School Connectedness program.

Bikeshare: Barriers, facilitators and impacts on car use

This thesis examined the factors contributing to bikeshare participation in Brisbane and Melbourne, and opportunities for increasing bikeshare usage. The degree to which bikeshare impacts on car use was also quantified. The findings of this program of research have implications for existing as well as planned bikeshare programs, both in Australia and abroad.

The impact of a congestion pricing exemption on the demand for new energy efficient vehicles in Stockholm

As governments seek to transition to more efficient vehicle fleets, one strategy has been to incentivize ‘green’ vehicle choice by exempting some of these vehicles from road user charges. As an example, to stimulate sales of Energy-Efficient Vehicles (EEVs) in Sweden, some of these automobiles were exempted from Stockholm’s congestion tax. In this paper the effect this policy had on the demand for new, privately-owned, exempt EEVs is assessed by first estimating a model of vehicle choice and then by applying this model to simulate vehicle alternative market shares under different policy scenarios. The database used to calibrate the model includes owner-specific demographics merged with vehicle registry data for all new private vehicles registered in Stockholm County during 2008. Characteristics of individuals with a higher propensity to purchase an exempt EEV were identified. The most significant factors included intra-cordon residency (positive), distance from home to the CBD (negative), and commuting across the cordon (positive). By calculating vehicle shares from the vehicle choice model and then comparing these estimates to a simulated scenario where the congestion tax exemption was inactive, the exemption was estimated to have substantially increased the share of newly purchased, private, exempt EEVs in Stockholm by 1.8% (+/- 0.3%; 95% C.I.) to a total share of 18.8%. This amounts to an estimated 10.7% increase in private, exempt EEV purchases during 2008 i.e. 519 privately owned, exempt EEVs.

Prediction of activity type in preschool children using machine learning techniques

Objectives Recent research has shown that machine learning techniques can accurately predict activity classes from accelerometer data in adolescents and adults. The purpose of this study is to develop and test machine learning models for predicting activity type in preschool-aged children. Design Participants completed 12 standardised activity trials (TV, reading, tablet game, quiet play, art, treasure hunt, cleaning up, active game, obstacle course, bicycle riding) over two laboratory visits. Methods Eleven children aged 3–6 years (mean age = 4.8 ± 0.87; 55% girls) completed the activity trials while wearing an ActiGraph GT3X+ accelerometer on the right hip. Activities were categorised into five activity classes: sedentary activities, light activities, moderate to vigorous activities, walking, and running. A standard feed-forward Artificial Neural Network and a Deep Learning Ensemble Network were trained on features in the accelerometer data used in previous investigations (10th, 25th, 50th, 75th and 90th percentiles and the lag-one autocorrelation). Results Overall recognition accuracy for the standard feed forward Artificial Neural Network was 69.7%. Recognition accuracy for sedentary activities, light activities and games, moderate-to-vigorous activities, walking, and running was 82%, 79%, 64%, 36% and 46%, respectively. In comparison, overall recognition accuracy for the Deep Learning Ensemble Network was 82.6%. For sedentary activities, light activities and games, moderate-to-vigorous activities, walking, and running recognition accuracy was 84%, 91%, 79%, 73% and 73%, respectively. Conclusions Ensemble machine learning approaches such as Deep Learning Ensemble Network can accurately predict activity type from accelerometer data in preschool children.