Edinburgh Napier University

  Introduction
Transportation is one of the main determinants of atmospheric pollutant emissions in urban areas. This externality has direct environmental, economic and public health consequences. This paper aims at investigating the space-time patterns of traffic air pollution in Balneário Camboriú (Brazil) over projected temporal scenarios and at estimating the damage costs of traffic air pollution to support transport policy-making.

Methods
To estimate the emission rates of pollutants, emission factors and traffic data were jointly used, whereas the pollutant concentrations were estimated using the Gaussian plume dispersion model. To identify the affected areas as well as possible spatial heterogeneity patterns of air pollution within clustered areas, an exploratory spatial analysis was also conducted. To assess the economic impact of air pollution, damage costs were calculated for various pollutants.

Results
The modeling results show that oxides of nitrogen (NO2) and oxides of sulphur (SO2) pollutants exceed the limits of air quality legislation, especially at a distance up to 10 meters from the roads, while 60% and 71% of the intersections are found to yield pollutant concentrations above the thresholds, primarily during peak hours. The analysis also confirmed that homogeneous traffic zones with similar emission rates are spatially clustered exhibiting positive autocorrelation patterns. The results of the economic appraisal showed that the estimated costs of traffic-related emissions were $0.89, $1.38 and $1.43 million/year, respectively, for the current, short-term and long-term scenarios.

Conclusions
This study serves as the first comprehensive analysis of traffic air pollution for the specific study region, providing implications and modeling tools that can be leveraged in public policies focusing on the elimination of the transportation-generated health burden. The developed analysis framework can also serve as a supporting tool for Public Agencies focusing on the high-level evaluation of traffic-related air pollution using limited and aggregate spatial and traffic data.