Abstract
Road vehicles are a major source of airborne nanoparticles (<100 nm) and particulate matter (PM), including PM10 (≤10 μm), PM2.5 (≤2.5 μm) and PM1 (≤1 μm) emissions. Over 99% of particles, by number, are reprsented by particles below 300 nm in diameter in polluted urban environments. The small size of particles in the nano-size range enables them to enter deeper into the lungs, causing both acute and chronic adverse health effects such as asthma, cardiovascular and ischemic heart diseases. The issue of air pollution becomes more prominent at urban traffic hot-spots such as traffic intersections (TIs), where pollution pockets are created due to frequently changing driving conditions. Recent trends suggest an exponential increase in travel demand and travelling time in the UK and elsewhere over the years, which indicate a growing need for the accurate characterisation of exposure at TIs since exposure at these hot-spots can contribute disproportionately high to overall commuting exposure. Based on field observations, this thesis aims (i) to investigate the traffic driving conditions in which TIs become a hotspot for nanoparticles and PM, (ii) to estimate the extent of road that is affected by high particle number concentrations (PNCs) and PM due to presence of a signal, (iii) to assess the vertical and horizontal variations in PNC and PMC at different TIs, (iv) to estimate the associated in-cabin and pedestrian exposure at TIs, and finally (v) to predict PNCs by using freely available models of air pollution at TIs. For this thesis, two sets of experiments (i.e. mobile- and fixed-sites) were carried out to measure airborne nanoparticles and PM in the size range of (0.005-10 μm) using a fast response differential mobility spectrometer (DMS50) and a GRIMM particle spectrometer (1.107 E). Mobile measurements were made on a circle passing through 10 TIs and fixed-site measurements were carried out at two different types of TIs (i.e. 3- and 4-way). Dispersion modelling was then performed by using California Line Source (CALINE4) and California Line Source for Queueing and Hotspot Calculations (CAL3QHC) at TIs. Several important findings were then extrapolated during the analysis. These findings indicated that congested TIs were found to become hot-spots when vehicle accelerate from idling conditions. The average length of road in longitudinal direction that is affected by high PNCs and PM was found to be highest (148 m; 89 to –59 m from the center of a TI) at a 3-way TI with built up area and lowest at 4-way TI with built-up area (79 m; 46 to –33 m). Vertical PNCs, horizontal PNCs and PM profiles followed an exponential decay. Exponential decay of PNCs in the vertical direction was much sharper at the 4-way TI than at the 3-way TI. Based on tracer gas method, particle number emission factors (PNEFs) during congested and free flow driving conditions were also estimated. The results showed that the PNEF during congested conditions can be up to 9 times higher than those during free flow conditions at a TI. In-cabin and pedestrian exposure during delay conditions was up to 7 and 7.3 times higher than exposure during free flow conditions at TIs. The modelling exercise showed that model choice to predict PNCs depends on the type of TI, size range of particles, receptor height and distance from the TI. Key findings of the proposed study could assist in validating and refining the capabilities of existing models for exposure assessment to PNCs at TIs. The proposed study will assist to enhance the scientific understanding of the problem as well as develop a database, showing the contribution of exposure at TIs towards the overall daily exposure during commuting in diverse city environments.