Spatiotemporal representativeness of air pollution monitoring in Dublin, Ireland.

The importance of selecting appropriate air pollution monitoring sites in a city is vital for accurately reporting air quality, enhancing the quality of high-resolution modelling and informing policy to implement measures to deliver cleaner air in the urban environment. COVID-19 restrictions impacted air quality in urban centres worldwide as reduced mobility led to changes in traffic-related air pollution (TRAP). As such, it offered a unique dataset to examine the spatial and temporal variations in air quality between monitoring stations in Dublin, Ireland. Firstly, an analysis of mobility data showed reductions across almost all sectors after COVID-19 restrictions came into place, which was expected to lower TRAP. In addition, similar changes in air quality were evident to other cities around the world: reductions in fine particulate matter (PM2.5) and nitrogen dioxide (NO2) concentrations and an increase in ozone (O3) concentrations. Average daily and diurnal concentrations for these three pollutants presented more statistically significant spatial and temporal changes during COVID-19 restrictions at monitoring sites with urban or traffic classifications than suburban background sites. Furthermore, substantial reductions in the range of average hourly pollutant concentrations were observed, 79% for PM2.5 and 75% for NO2, with a modest 24% reduction for O3. Correlation analysis of air pollution between monitoring sites and years demonstrated an improvement in the R2 for NO2 concentrations only, suggesting that spatiotemporal homogeneity was most notable for this TRAP due to mobility restrictions during COVID-19. The spatiotemporal representativeness of monitoring stations across the city will change with greener transport, and air quality during COVID-19 can provide a benchmark to support the introduction of new policies for cleaner air.

Modelling personal exposure to particulate air pollution: an assessment of time-integrated activity modelling, Monte Carlo simulation & artificial neural network approaches.

An experimental assessment of personal exposure to PM10 in 59 office workers was carried out in Dublin, Ireland. 255 samples of 24-h personal exposure were collected in real time over a 28 month period. A series of modelling techniques were subsequently assessed for their ability to predict 24-h personal exposure to PM10. Artificial neural network modelling, Monte Carlo simulation and time-activity based models were developed and compared. The results of the investigation showed that using the Monte Carlo technique to randomly select concentrations from statistical distributions of exposure concentrations in typical microenvironments encountered by office workers produced the most accurate results, based on 3 statistical measures of model performance. The Monte Carlo simulation technique was also shown to have the greatest potential utility over the other techniques, in terms of predicting personal exposure without the need for further monitoring data. Over the 28 month period only a very weak correlation was found between background air quality and personal exposure measurements, highlighting the need for accurate models of personal exposure in epidemiological studies.

The passive control of air pollution exposure in Dublin, Ireland: a combined measurement and modelling case study.

This study investigates the potential real world application of passive control systems to reduce personal pollutant exposure in an urban street canyon in Dublin, Ireland. The implementation of parked cars and/or low boundary walls as a passive control system has been shown to minimise personal exposure to pollutants on footpaths in previous investigations. However, previous research has been limited to generic numerical modelling studies. This study combines real-time traffic data, meteorological conditions and pollution concentrations, in a real world urban street canyon before and after the implementation of a passive control system. Using a combination of field measurements and numerical modelling this study assessed the potential impact of passive controls on personal exposure to nitric oxide (NO) concentrations in the street canyon in winter conditions. A calibrated numerical model of the urban street canyon was developed, taking into account the variability in traffic and meteorological conditions. The modelling system combined the computational fluid dynamic (CFD) simulations and a semi-empirical equation, and demonstrated a good agreement with measured field data collected in the street canyon. The results indicated that lane distribution, fleet composition and vehicular turbulence all affected pollutant dispersion, in addition to the canyon geometry and local meteorological conditions. The introduction of passive controls displayed mixed results for improvements in air quality on the footpaths for different wind and traffic conditions. Parked cars demonstrated the most comprehensive passive control system with average improvements in air quality of up to 15% on the footpaths. This study highlights the potential of passive controls in a real street canyon to increase dispersion and improve air quality at street level.

Environmental tobacco smoke in designated smoking areas in the hospitality industry: exposure measurements, exposure modelling and policy assessment.

Tobacco control policy has been enacted in many jurisdictions worldwide banning smoking in the workplace. In the hospitality sector many businesses such as bars, hotels and restaurants have installed designated smoking areas on their premises and allowance for such smoking areas has been made in the tobacco control legislation of many countries. An investigation was carried out into the level of exposure to environmental tobacco smoke (ETS) present in 8 pubs in Ireland which included designated smoking areas complying with two different definitions of a smoking area set out in Irish legislation. In addition, ETS exposure in a pub with a designated smoking area not in compliance with the legislation was also investigated. The results of this investigation showed that the two differing definitions of a smoking area present in pubs produced similar concentrations of benzene within smoking areas (5.1-5.4 µg/m(3)) but differing concentrations within the 'smoke-free' areas (1.42-3.01 µg/m(3)). Smoking areas in breach of legislative definitions were found to produce the highest levels of benzene in the smoking area (49.5 µg/m(3)) and 'smoke-free' area (7.68 µg/m(3)). 3D exposure modelling of hypothetical smoking areas showed that a wide range of ETS exposure concentrations were possible in smoking areas with the same floor area and same smoking rate but differing height to width and length to width ratios. The results of this investigation demonstrate that significant scope for improvement of ETS exposure concentrations in pubs and in smoking areas may exist by refining and improving the legislative definitions of smoking areas in law.

A numerical investigation of the impact of low boundary walls on pedestrian exposure to air pollutants in urban street canyons.

A previous investigation into methods of exposure reduction for the pedestrian in the urban commuter environment highlighted the impact of a low boundary wall on the dispersion of air pollutants from adjacent traffic sources. The impact of low boundary walls on the dispersion of air pollutants in street canyons has been brought forward in this investigation to examine them, in more generic terms, with a view to highlighting exposure reduction strategies for pedestrians. 3D Computational Fluid Dynamics (CFD) models were used to examine this effect for varying wind speeds and directions in different street canyon geometries. The results of this investigation show that a low boundary wall located at the central median of the street canyon creates a significant reduction in pedestrian exposure on the footpath. Reductions of up to 40% were found for perpendicular wind directions and up to 75% for parallel wind directions, relative to the same canyon with no wall. The magnitude of the exposure reduction was also found to vary according to street canyon geometry and wind speed.

Reduced exposure to air pollution on the boardwalk in Dublin, Ireland. Measurement and prediction.

This paper outlines an air pollution study carried out on Dublin city's recently completed boardwalk along the side of and overhanging the River Liffey. Air quality samples were taken along the length of the boardwalk to investigate whether pedestrians using the boardwalk would have a lower air pollution exposure than those using the adjoining footpath along the road. The results of the study show significant reductions in pedestrian exposure to both traffic derived particulates and hydrocarbons along the boardwalk as opposed to the footpath. Computational fluid dynamics was also used to model the outcome of these field measurements and shows the importance of the boundary wall between the footpath and boardwalk in reducing air pollution exposure for the pedestrian, the results of which are also presented herein.