The Effect of Route Choice in Children's Exposure to Ultrafine Particles Whilst Walking to School

Disparities in air pollution exposure among primary schools in Auckland: a geo-spatial analysis

Outdoor air pollution poses a significant threat to children, especially those in low socioeconomic areas exposed to dense traffic pollutants. This study explores the relationship between socioeconomic status (SES), ethnicity, and air pollution exposure among primary school children in Auckland, New Zealand. Findings indicate that NO₂ levels do not vary significantly between schools in low versus high SES areas; however, Pacifica children experience the highest exposure, with levels reaching up to 13.37 μg/m³. Central regions of Auckland show particularly high pollution levels, measuring 15.7 μg/m³-significantly above the regional average of 13.16 μg/m³, which amplifies health risks for children in these areas. These findings underscore the critical need for targeted interventions to mitigate the adverse effects of air pollution. Future research should broaden the scope to include more pollutants and utilize more recent data to assess the health impacts of air pollution.   .

Evaluating the efficacy of targeted traffic management interventions: A novel methodology for determining the composition of particulate matter in urban air pollution hotspots

Worldwide, there is an increasing uptake of traffic management interventions aimed at reducing the impact of traffic related air pollution on public health. However, the evidence base linking the proposed changes with the resulting improvements in air quality is lacking. In this paper we present data from a micro-network of low-cost PM10 samplers collected from an isolated urban centre (Auckland, New Zealand). The data was then analysed using a new combination of analytical methods aimed to identify the composition and hence, the source of pollution. Whilst across the three sites mass concentration of PM10 and black carbon were similar, Raman spectroscopy successfully identified variations in the soot composition at different sites, enabling some particulate matter to be linked to diesel vehicle emissions. A mass reconstruction approach proved useful in determining that the airshed is well-mixed and also highlighted the impacts of urban design on recorded concentrations. The results show that networks of low-cost sensors, combined with the range of analytical techniques used here can help policymakers test the efficacy of interventions and management strategies designed to combat the burden of air pollution on public health.

The impact of low emission zones on personal exposure to ultrafine particles in the commuter environment

Auckland is a city with limited industrial activity, road traffic being the dominant source of air pollution. Thus, the time periods when social contact and movement in Auckland were severely curtailed due to COVID-19 restrictions presented a unique opportunity to observe impacts on pedestrian exposure to air pollution under a range of different traffic flow scenarios, providing insights into the impacts of potential future traffic calming measures. Pedestrian exposure to ultrafine particles (UFPs), was measured using personal monitoring along a customised route through Central Auckland during different COVID-19-affected traffic flow conditions. Results showed that reduced traffic flows led to statistically significant reductions in average exposure to UFP under all traffic reduction scenarios (TRS). However, the size of the reduction was variable in both time and place. Under the most stringent TRS (traffic reduction of 82 %), median ultrafine particle (UFP) concentrations reduced by 73 %. Under the less stringent scenario, the extent of reduction varied in time and space; a traffic reduction of 62 % resulted in a 23 % reduction in median UFP concentrations in 2020 but in 2021 similar traffic reductions led to a decrease in median UFP concentrations of 71 %. Under all scenarios, the magnitude of the impact of traffic reductions on UFP exposure varied along the route, with areas dominated by emissions from construction and ferry/port activities showing little correlation between traffic flow and exposure. Shared traffic spaces, previously pedestrianised, also recorded consistently high concentrations with little variability observed. This study provided a unique opportunity to assess the potential benefits and risks of such zones and to help decision-makers evaluate future traffic management interventions (such as low emissions zones). The results suggest that controlled traffic flow interventions can result in a significant reduction in pedestrian exposure to UFPs, but that the magnitude of reductions is sensitive to local-scale variations in meteorology, urban land use and traffic flow patterns.

Prediction of Short-Term Ultrafine Particle Exposures Using Real-Time Street-Level Images Paired with Air Quality Measurements

Within-city ultrafine particle (UFP) concentrations vary sharply since they are influenced by various factors. We developed prediction models for short-term UFP exposures using street-level images collected by a camera installed on a vehicle rooftop, paired with air quality measurements conducted during a large-scale mobile monitoring campaign in Toronto, Canada. Convolutional neural network models were trained to extract traffic and built environment features from images. These features, along with regional air quality and meteorology data were used to predict short-term UFP concentration as a continuous and categorical variable. A gradient boost model for UFP as a continuous variable achieved R² = 0.66 and RMSE = 9391.8#/cm³ (mean values for 10-fold cross-validation). The model predicting categorical UFP achieved accuracies for "Low" and "High" UFP of 77 and 70%, respectively. The presence of trucks and other traffic parameters were associated with higher UFPs, and the spatial distribution of elevated short-term UFP followed the distribution of single-unit trucks. This study demonstrates that pictures captured on urban streets, associated with regional air quality and meteorology, can adequately predict short-term UFP exposure. Capturing the spatial distribution of high-frequency short-term UFP spikes in urban areas provides crucial information for the management of near-road air pollution hot spots.