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Background: Links between air pollution and asthma are less well established for older adults than some younger groups. Nitrogen dioxide (NO2) concentrations are widely used as an indicator of transport-related air pollution, and some literature suggests NO2 may directly affect asthma.Methods: This study used data on 8162 adults >50 years old in the Republic of Ireland to model associations between estimated annual outdoor concentration of NO2 and the probability of having asthma. Individual-level geo-coded survey data from The Irish Longitudinal Study on Ageing (TILDA) were linked to model-based estimates of annual average NO2 at 50 m resolution. Asthma was identified using two methods: self-reported diagnoses and respondents' use of medications related to obstructive airway diseases. Logistic regressions were used to model the relationships.Results: NO2 concentrations were positively associated with the probability of asthma [marginal effect (ME) per 1 ppb of airborne NO2 = 0.24 percentage points asthma self-report, 95% confidence interval (CI) 0.06-0.42, mean asthma prevalence 0.09; for use of relevant medications ME = 0.21 percentage points, 95% CI 0.049-0.37, mean prevalence 0.069]. Results were robust to varying model specification and time period. Respondents in the top fifth percentile of NO2 exposure had a larger effect size but also greater standard error (ME = 2.4 percentage points asthma self-report, 95% CI -0. 49 to 5.3).Conclusions: Associations between local air pollution and asthma among older adults were found at relatively low concentrations. To illustrate this, the marginal effect of an increase in annual average NO2 concentration from sample minimum to median (2.5 ppb) represented about 7-8% of the sample average prevalence of asthma. [ABSTRACT FROM AUTHOR]

Background: The harmful effects of outdoor air pollution on stroke incidence are becoming increasingly recognised. We examined the impact of different air pollutants (PM2.5, PM10, NO2, ozone, and SO2) on admission for all strokes in two Irish urban centres from 2013 to 2017. Methods: Using an ecological time series design with Poisson regression models, we analysed daily hospitalisation for all strokes and is-chaemic stroke by residence in Dublin or Cork, with air pollution level monitoring data with a lag of 0–2 days from exposure. Splines of temperature, relative humidity, day of the week, and time were included as confounders. Analysis was also performed across all four seasons. Data are presented as relative risks (RRs) and 95% confidence intervals (95% CI) per interquartile range (IQR) increase in each pollutant. Results: There was no significant association between all stroke admission and any individual air pollutant. On seasonal analysis, during winter in the larger urban centre (Dublin), we found an association between all stroke cases and an IQR increase in NO2 (RR 1.035, 95% CI: 1.003–1.069), PM10 (RR 1.032, 95% CI: 1.007–1.057), PM2.5 (RR 1.024, 95% CI: 1.011–1.039), and SO2 (RR 1.035, 95% CI: 1.001–1.071). There was no significant association found in the smaller urban area of Cork. On meta-analysis, there remained a significant association between NO2 (RR 1.013, 95% CI: 1.001–1.024) and PM2.5 (1.009, 95% CI 1.004–1.014) per IQR increase in each. Discussion: Short-term air pollution in winter was found to be associated with hospitalisation for all strokes in a large urban centre in Ireland. As Ireland has relatively low air pollution internationally, this highlights the need to introduce policy changes to reduce air pollution in all countries. [ABSTRACT FROM AUTHOR]

More than half of British voters chose to leave the European Union (EU) leading to a series of negotiations between the United Kingdom and the EU. The withdrawal of the UK from the EU is widely referred to as Brexit. As the only country that shares a land border with the UK, the impact of Brexit on Ireland is expected to be greater than on any other European country. The objective of the research is to evaluate the potential impact of Brexit on the transport sector in Ireland at a micro level by focusing on cross‐border commuters and by also assessing the impact on road freight transport. Potential crossing scenarios are examined at six crossing locations. Assuming a hard border is implemented, each crossing is modelled in VISSIM, a microscopic traffic flow simulation software, using traffic data from Transport Infrastructure Ireland (TII) and dwell time estimated based on the US–Canada border crossings. Six scenarios are considered to determine the impact on cross‐border traffic at different flow conditions and with varying levels of technology used in border infrastructure leading to short versus long processing times. The paper evaluates travel measures including delays, queue lengths and emissions. The worst‐case scenario has a vehicle delay of 18.4 min and the highest delay‐associated costs across all locations modelled are estimated at €60.7 million per year. Estimated emissions generated at the border crossings raise concerns about environmental impacts of a hard Brexit. Interviews with stakeholders emphasized the critical role of technology in reducing the impact of a hard Brexit on cross‐border commuters and on the freight sector. A key finding is the importance of using technology tools to facilitate controls and reduce processing times. The results indicate that technology use leads to significant time and cost savings as well as reduced environmental impacts. [ABSTRACT FROM AUTHOR]

Background Fine particulate matter (PM2.5) has been associated with disease incidence worldwide. In Ireland this is mainly produced by residential heating systems, particularly peat, coal and wood. This study aimed to explore the relationship between short-term exposure to PM2.5 and hospital admissions due to stroke, atrial fibrillation, myocardial infarction, atrial fibrillation (AF), heart failure, chronic obstructive pulmonary disease (COPD), asthma, Parkinson's disease, dementia and hip fracture in Dublin City and County between 2013 and 2017. Methods This was an ecological time series design utilising routine hospitalisation data collected from the national Health Service Executive (Hospital In-Patient Enquiry (HIPE)). Incidence of hospitalisation for each disease was identified by county of residence. Mean daily PM2.5 levels for Dublin were calculated using monitoring data from the Environmental Protection Agency's four monitoring sites. Disease incidence was organised by mean PM2.5 levels into 10μg/m3 categories and analysed using Poisson regression models correcting for minimum daily temperature at a lag of zero to five days. Results There was a significant increase in the short-term incidence of acute ischaemic stroke, AF, heart failure, Parkinson's disease, dementia and COPD when PM2.5 levels were above 50μg/m3 compared to when levels were below 10μg/m3 at one day post exposure when correcting for minimum temperature. Conclusion Controls need to be brought in to ensure that PM2.5 does not exceed a 50μg/m3 level due to the increase in disease incidence associated with same. The urban burning of solid fuels should be severely restricted. [ABSTRACT FROM AUTHOR]

Irish rural areas saw an increase in the number of burglaries in the period following the completion of a network of high speed motorway interurban routes. To test the hypothesis that the new fast infrastructure was providing quick exits by urban based criminal gangs, Irish crime statistics along with census data were combined in a logistic regression analysis to assess the relative influence of accessibility, deprivation, population, and proximity to fast road infrastructure on the number of burglaries in areas. It was found that accessibility had a higher influence on crime than area deprivation and that proximity to fast road infrastructure was not significant. [ABSTRACT FROM AUTHOR]

Abstract: The Irish government has outlined plans for 10% of the national road fleet to be powered by electricity by 2020. The objective of this paper is to evaluate the potential reduction in road traffic related emissions due to commuting in the Greater Dublin Area under different electric vehicle market penetration scenarios. The results indicate that the introduction of electric vehicles offers the potential for reductions in all road traffic related emissions. However, the time required for electric vehicles to acquire a significant share of the fleet, suggests that they will have a limited impact on climate change and urban air quality for at least the next decade. [Copyright &y& Elsevier]

The paper reports on research using a new type of pedestrian waiting countdown timer to influence pedestrian behaviour at signalised pedestrian crossings in Dublin. The aim was to evaluate the impact of the timers on pedestrian crossing behaviour and in particular to see if it had any impact on the number of illegal crossings (during red man––do not walk signal). The timers inform the pedestrian how many seconds they have to wait until the green man appears. Two surveys were used to evaluate the impact: an attitude survey to evaluate the perception of the users and a video survey to estimate quantitatively the impacts on pedestrian behaviour but also to evaluate the awareness levels of the pedestrians towards the countdown timers. Some of the results include observance of more compliant behaviour by females and that pedestrians tend to overestimate their waiting time. Before the timers were installed 65% of pedestrians started to cross during the green man and amber phases but this rose to 76% after the timers were installed. [Copyright &y& Elsevier]

The objective of the work was to evaluate the potential user response to distance and time based road pricing of a sample of individuals drawn randomly from a group of volunteers in Dublin. The road use pricing charge levels were selected to match the marginal external costs of car transport i.e. those costs not currently paid by the car user. Such costs include marginal external costs of congestion, air pollution and noise. The project formed part of the EU DGXVII EUROPRICE project where one of the objectives was to evaluate the impact of road use pricing on private transport demand. Estimates of the marginal external costs of car travel had been previously made for Dublin in an EU DGVII project entitled TRENEN II STRAN and the results were used to select the road pricing charges in the trial. The distance travelled and travel time of a particular individual's work trip were noted. Charges per unit distance and time were applied so that the individual would incur a total charge for their average peak period work trip of 6.4 euro; the average marginal external cost of a peak period trip in Dublin, as estimated by the TRENEN model. Although the sample of individuals was relatively small, the indications from the results are worthy of note and further investigation on a larger sample. A significant reduction in the number of peak period trips was evident, of the order of 22%, resulting from trip suppression and transfer to other modes. [ABSTRACT FROM AUTHOR]

• Developed wind sector land use regression model to estimate nitrogen dioxide (NO 2) • Inclusion of varying vehicle type emission rates an improvement on existing models. • Method transferrable to land use regression models that include distance travelled. • Application of model to NO 2 mitigation strategies also demonstrated. • Removal of diesel from public service fleet achieved NO 2 reduction of 0.3–1.9 μg/m3. The transport sector has been identified as one of the main contributors to nitrogen dioxide (NO 2) pollution in Ireland. This research develops an enhanced Wind Sector Land Use Regression (WS-LUR) model to estimate NO 2 concentrations across Ireland, in areas where air pollution monitoring is not available. The model incorporates details of the vehicle fleet breakdown to weight vehicle type flows based on the emission rates of the vehicle type, differentiating routes with varying proportions of heavier emitting vehicles. In 2008, car taxation underwent a significant change from an engine size based system to a carbon dioxide (CO 2) emission rate based system resulting in a significant transition towards diesel fuelled vehicles. A mitigation strategy to remove diesel fuelled vehicles from the public service vehicle fleet was tested achieving predicted NO 2 reductions in the range of 0.3 μg/m3 to 1.9 μg/m3. The impact of COVID-19 on NO 2 concentration levels was also investigated. [ABSTRACT FROM AUTHOR]

Concerns have been expressed regarding the displacement of harmful emissions from internal combustion engine vehicle (ICEV) tailpipes to the sources of electricity generation used to charge electric vehicles (EV). The degree to which EVs can reduce the environmental impacts of road transportation is dependent on the fuel mix of electricity generation within a country and on the real-time charging behaviours of EV users since the fuel mix of electricity generation frequently changes. This paper analyses the varying environmental impacts of EVs based on contrasting user behaviours and compares them to the environmental impacts of ICEVs. Individual EV user profiles are developed which comprise real data emerging from charge events undertaken in Ireland, and information is gathered on the actual CO 2 intensity of the electrical grid in real-time, allowing for the carbon intensity of every individual charge event to be determined using time and date information. The results show that the environmental impacts of EVs are highly influenced by the charging behaviours of individual users, and night-time charging was found to produce the largest environmental impact. EVs are shown to be a more environmentally friendly choice of vehicle than ICEVs under a wide majority of scenarios. [ABSTRACT FROM AUTHOR]

Car-sharing services offer potential to reduce dependency on private cars, and their electrification may decarbonise the transportation sector even further. This study estimates the potential emission reduction if shared cars operated by GoCar- a car-sharing service in Ireland- are electrified and assesses which trips could be completed using shared electric vehicles (EVs). Based on historical and targeted growth scenarios, appropriate forecasting methods were explored to predict GoCar's fleet size and travel distance for 2030. The corresponding emissions were estimated using COPERT. Results showed that electrifying half of the GoCar fleet by 2030 can reduce total emissions by up to 45% compared with baseline, whereas emissions were elevated by 50% compared to 2021 fleet operations. Results also suggest that the majority (70% to 90%) of GoCar day bookings can be completed using the available EVs in the Irish market, indicating the feasibility of EVs in car-sharing services. [ABSTRACT FROM AUTHOR]

This paper examines the charge and trip making behaviour of a fleet of electric vehicle (EV) users in Ireland. Through the analysis of real data from data loggers located within the EVs, valuable information is obtained on trip event characteristics, consumer preferences, timing and consumption patterns of charge events. The findings from this trial can be used to inform infrastructure providers in other small and medium size cities and in suburban or rural settings. An understanding of the likely usage patterns of EV users is critical for the rollout of charging infrastructure. Vehicles were separated into private use and business use vehicles, and the timings of EV usage events were divided into weekday and weekend events. Along with a descriptive analysis of the results, interquartile range (IQR) and analysis of variance (ANOVA) analyses were employed to quantify and characterise EV user behaviour. An early morning peak in charging behaviour was identified, and state of charge (SOC), charge consumption, and time and distance since last charge analyses indicate EV users charge more frequently than required. Trip event patterns identify the fact that EVs are generally available to be charged overnight, reducing demand on the electrical grid during peak hours. Trip distance analyses show that EVs are typically driven short distances, confirming their suitability to urban driving environments. The results can not only account for the effects of EV integration into the Irish vehicle fleet, but it can also provide information on the likely impacts of mass integration into European energy systems. [ABSTRACT FROM AUTHOR]

Background: Links between air pollution and asthma are less well established for older adults than some younger groups. Nitrogen dioxide (NO2) concentrations are widely used as an indicator of transport-related air pollution, and some literature suggests NO2 may directly affect asthma., Methods: This study used data on 8162 adults >50 years old in the Republic of Ireland to model associations between estimated annual outdoor concentration of NO2 and the probability of having asthma. Individual-level geo-coded survey data from The Irish Longitudinal Study on Ageing (TILDA) were linked to model-based estimates of annual average NO2 at 50 m resolution. Asthma was identified using two methods: self-reported diagnoses and respondents' use of medications related to obstructive airway diseases. Logistic regressions were used to model the relationships., Results: NO2 concentrations were positively associated with the probability of asthma [marginal effect (ME) per 1 ppb of airborne NO2 = 0.24 percentage points asthma self-report, 95% confidence interval (CI) 0.06-0.42, mean asthma prevalence 0.09; for use of relevant medications ME = 0.21 percentage points, 95% CI 0.049-0.37, mean prevalence 0.069]. Results were robust to varying model specification and time period. Respondents in the top fifth percentile of NO2 exposure had a larger effect size but also greater standard error (ME = 2.4 percentage points asthma self-report, 95% CI -0. 49 to 5.3)., Conclusions: Associations between local air pollution and asthma among older adults were found at relatively low concentrations. To illustrate this, the marginal effect of an increase in annual average NO2 concentration from sample minimum to median (2.5 ppb) represented about 7-8% of the sample average prevalence of asthma., (© The Author(s) 2020; all rights reserved. Published by Oxford University Press on behalf of the International Epidemiological Association.)

Parks are an important part of the urban fabric of cities. They offer people the opportunity to connect with nature, engage in physical activity, find a haven away from the city noise, or spend time alone or with family and friends. This study examines the relative importance of park and park visit characteristics for 865 survey participants in Dublin, Ireland. The data is analyzed using a multinomial logistic regression model which can distinguish the relative importance of attributes. The model results demonstrate an improvement over proportional by chance accuracy, indicating that the model is useful. The results suggest that when and why individuals go to the park along with the proximity of their residence to the park influence visit frequency more than their age and gender and more than their impression of the sound levels in the park. The contribution of the results, in terms of their potential usefulness to planners, suggest that the priority should be on the provision of park space close to residential areas, so that individuals can engage in activities such as walking and relaxation, and that the quality of that space, in the context of noise levels at least, is less important.