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

Abstract

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.