Model for predicting 2D spatial distribution of air pollutant concentrations in streets and roundabouts

Source abstract

This paper presents an innovative methodology that combines Smart City concepts with atmospheric dispersion modelling for the control and management of traffic-related air pollution on urban environments. Road traffic has become one of the main anthropogenic sources of air pollution in cities, while municipal authorities often lack the resources or knowledge required to develop and implement advanced strategies, techniques and tools to manage air quality problems. To address this challenge, a calculation method was developed to model and predict two-dimensional spatial profiles of atmospheric concentrations, both along and across roads, in large avenues and roundabouts within urban centres. The model is based on the Gaussian dispersion formula and provides a simple, easy-to-apply and computationally efficient tool that does not require the use of complex software. Following a detailed prior field sampling campaign, it can be readily implemented in urban environments with limited technical resources. In addition, this novel methodology enables the identification of population risk areas and establishes a correlation between pollutant levels and traffic flow on each street and roundabout. Key characteristic parameters associated with traffic-derived emissions, such as critical distances and vehicle flow rates, can also be estimated. Furthermore, the model allows to identify optimal locations for atmospheric monitoring stations or devices on roads. The proposed strategy was applied and validated in the main avenues and roundabouts of a medium-sized city for VOCs, NO 2 , PM 10 and PM 2.5 . The results demonstrated that the model provides reliable predictions of pollutant spatial distributions and constitutes a useful, accessible and valuable tool for local or political decision-makers.