Transport energy demand: techno-economic modelling and scenarios for Irish climate policy

The case for energy policy modelling is strong in Ireland, where stringent EU climate targets are projected to be overshot by 2015. Policy targets aiming to deliver greenhouse gas and renewable energy targets have been made, but it is unclear what savings are to be achieved and from which sectors. Concurrently, the growth of personal mobility has caused an astonishing increase in CO2 emissions from private cars in Ireland, a 37% rise between 2000 and 2008, and while there have been improvements in the efficiency of car technology, there was no decrease in the energy intensity of the car fleet in the same period. This thesis increases the capacity for evidenced-based policymaking in Ireland by developing techno-economic transport energy models and using them to analyse historical trends and to project possible future scenarios. A central focus of this thesis is to understand the effect of the car fleet‘s evolving technical characteristics on energy demand. A car stock model is developed to analyse this question from three angles: Firstly, analysis of car registration and activity data between 2000 and 2008 examines the trends which brought about the surge in energy demand. Secondly, the car stock is modelled into the future and is used to populate a baseline “no new policy” scenario, looking at the impact of recent (2008-2011) policy and purchasing developments on projected energy demand and emissions. Thirdly, a range of technology efficiency, fuel switching and behavioural scenarios are developed up to 2025 in order to indicate the emissions abatement and renewable energy penetration potential from alternative policy packages. In particular, an ambitious car fleet electrification target for Ireland is examined. The car stock model‘s functionality is extended by linking it with other models: LEAP-Ireland, a bottom-up energy demand model for all energy sectors in the country; Irish TIMES, a linear optimisation energy system model; and COPERT, a pollution model. The methodology is also adapted to analyse trends in freight energy demand in a similar way. Finally, this thesis addresses the gap in the representation of travel behaviour in linear energy systems models. A novel methodology is developed and case studies for Ireland and California are presented using the TIMES model. Transport Energy

Private health care coverage and increased risk of obstetric intervention

Background: When clinically indicated, common obstetric interventions can greatly improve maternal and neonatal outcomes. However, variation in intervention rates suggests that obstetric practice may not be solely driven by case criteria. Methods: Differences in obstetric intervention rates by private and public status in Ireland were examined using nationally representative hospital discharge data. A retrospective cohort study was performed on childbirth hospitalisations occurring between 2005 and 2010. Multivariate logistic regression analysis with correction for the relative risk was conducted to determine the risk of obstetric intervention (caesarean delivery, operative vaginal delivery, induction of labour or episiotomy) by private or public status while adjusting for obstetric risk factors. Results: 403,642 childbirth hospitalisations were reviewed; approximately one-third of maternities (30.2%) were booked privately. After controlling for relevant obstetric risk factors, women with private coverage were more likely to have an elective caesarean delivery (RR: 1.48; 95% CI: 1.45-1.51), an emergency caesarean delivery (RR: 1.13; 95% CI: 1.12-1.16) and an operative vaginal delivery (RR: 1.25; 95% CI: 1.22-1.27). Compared to women with public coverage who had a vaginal delivery, women with private coverage were 40% more likely to have an episiotomy (RR: 1.40; 95% CI: 1.38-1.43). Conclusions: Irrespective of obstetric risk factors, women who opted for private maternity care were significantly more likely to have an obstetric intervention. To better understand both clinical and non-clinical dynamics, future studies of examining health care coverage status and obstetric intervention would ideally apply mixed-method techniques.