What is the energy balance of grass biomethane in Ireland and other temperate northern European climates?

Biofuels have had bad press in recent years. There are primarily two distinct issues. The biofuel crops with the best yields (such as sugarcane or oil palm) grow in tropical countries where habitat destruction has occurred in association with the biofuel system. First generation indigenous energy crops commonly used for transport fuel in Europe (such as rapeseed and wheat) have low yields and/or the energy balance of the associated biofuel system is poor. This paper shows that grass is a crop with significant yields and grass biomethane (a gaseous renewable transport biofuel) has a very good energy balance and does not involve habitat destruction, land use change, new farming practices or annual tilling. The gross and net energy production per hectare are almost identical to palm oil biodiesel; the net energy of the grass system is at least 50% better than the next best indigenous European biofuel system investigated. Ten percent of Irish grasslands could fuel over 55% of the Irish private car fleet. © 2009 Elsevier Ltd. All rights reserved.

A Community Study of the Psychological Effects of the Omagh Car Bomb on Adults

Background: The main aims of the study were to assess psychological morbidity among adults nine months after a car bomb explosion in the town of Omagh, Northern Ireland and to identify predictors of chronic posttraumatic stress disorder symptoms.

Method: A questionnaire was sent to all adults in households in The Omagh District Council area. The questionnaire comprised established predictors of PTSD (such as pre-trauma personal characteristics, type of exposure, initial emotional response and long-term adverse physical or financial problems), predictors derived from the Ehlers and Clark (2000) cognitive model, a measure of PTSD symptoms and the General Health Questionnaire.

Results: Among respondents (n = 3131) the highest rates of PTSD symptoms and probable casesness (58.5%) were observed among people who were present in the street when the bomb exploded but elevated rates were also observed in people who subsequently attended the scene (21.8% probable caseness) and among people for whom someone close died (11.9%). People with a near miss (left the scene before the explosion) did not show elevated rates. Exposure to the bombing increased PTSD symptoms to a greater extent than general psychiatric symptoms. Previously established predictors accounted for 42% of the variance in PTSD symptoms among people directly exposed to the bombing. Predictors derived from the cognitive model accounted for 63%.

Conclusions: High rates of chronic PTSD were observed in individuals exposed to the bombing. Psychological variables that are in principle amenable to treatment were the best predictors of PTSD symptoms. Teams planning treatment interventions for victims of future bombings and other traumas may wish to take these results into account.

Quantifying the Energy & carbon emissions implications of a 10% electric vehicles target

EU Directive 2009/28/EC on Renewable Energy requires each Member State to ensure 10% of transport energy (excluding aviation and marine transport) comes from renewable sources by 2020 (10% RES-T target). In addition to the anticipated growth in biofuels, this target is expected to be met by the increased electrification of transport coupled with a growing contribution from renewable energy to electricity generation. Energy use in transport accounted for nearly half of Ireland’s total final energy demand and about a third of energy-related carbon dioxide emissions in 2007. Energy use in transport has grown by 6.3% per annum on average in the period 1990 – 2007. This high share and fast growth relative to other countries highlights the challenges Ireland faces in meeting ambitious renewable energy targets. The Irish Government has set a specific target for Electric Vehicles (EV) as part of its strategy to deliver the 10% RES-T target. By 2020, 10% of all vehicles in its transport fleet are to be powered by electricity. This paper quantifies the impacts on energy and carbon dioxide emissions of this 10% EV target by 2020. In order to do this an ‘EV Car Stock’ model was developed to analyse the historical and future make-up of the passenger car portion of the fleet to 2025. Three scenarios for possible take-up in EVs were examined and the associated energy and emissions impacts are quantified. These impacts are then compared to Ireland’s 10% RES-T target and greenhouse gas (GHG) emissions reduction targets for 2020. Two key findings of the study are that the 10% EV target contributes 1.7% to the 10% RES-T target by 2020 and 1.4% to the 20% reduction in Non-ETS emissions by 2020 relative to 2005.

Access to a Car and the Self-Reported Health and Mental Health of People Aged 65 and Older in Northern Ireland

This article examines relationships between access to a car and the self- reported health and mental health of older people. The analysis is based on a sample of N 1⁄4 65,601 individuals aged 65 years and older from the Northern Ireland Longitudinal Study linked to 2001 and 2011 census returns. The findings from hierarchical linear and binary logistic multilevel path models indicate that having no access to a car is related to a considerable health and mental health disadvantage particularly for older people who live alone. Rural–urban health and mental health differences are mediated by access to a car. The findings support approaches that emphasize the importance of autonomy and independence for the well-being of older people and indicate that not having access to a car can be a problem for older people not only in rural but also in intermediate and urban areas, if no sufficient alternative forms of mobility are provided.

Identification of Road Irregularities via Vehicle Accelerations

A periodic monitoring of the pavement condition facilitates a cost-effective distribution of the resources available for maintenance of the road infrastructure network. The task can be accurately carried out using profilometers, but such an approach is generally expensive. This paper presents a method to collect information on the road profile via accelerometers mounted in a fleet of non-specialist vehicles, such as police cars, that are in use for other purposes. It proposes an optimisation algorithm, based on Cross Entropy theory, to predict road irregularities. The Cross Entropy algorithm estimates the height of the road irregularities from vehicle accelerations at each point in time. To test the algorithm, the crossing of a half-car roll model is simulated over a range of road profiles to obtain accelerations of the vehicle sprung and unsprung masses. Then, the simulated vehicle accelerations are used as input in an iterative procedure that searches for the best solution to the inverse problem of finding road irregularities. In each iteration, a sample of road profiles is generated and an objective function defined as the sum of squares of differences between the ‘measured’ and predicted accelerations is minimized until convergence is reached. The reconstructed profile is classified according to ISO and IRI recommendations and compared to its original class. Results demonstrate that the approach is feasible and that a good estimate of the short-wavelength features of the road profile can be detected, despite the variability between the vehicles used to collect the data.