Kriging method application and traffic behavior profiles from local radar network database: A proposal to support traffic solutions and air pollution control strategies

Abstract

Vehicles are commonly the main source of outdoor air pollution in urban areas and vehicular emission inventory is a tool to identify the emissions contribution from mobile sources. In this study, we developed an emission inventory to Belo Horizonte, a densely populated urban city in Brazil, with approximately 2.0 million vehicles. The vehicular emission inventory was developed applying the National Vehicle Emission Inventory model (VEIN) using emission factor from São Paulo State Environmental Protection Agency, different traffic behavior profile (constant and different diurnal cycle per vehicle type) established from local radar data and kriging interpolation method considering four different scenarios with reductions in fleet composition. The scenarios were described as according the combination between traffic behavior profiles, vehicle flow, vehicle type and a fuel consumption. The comparison between scenarios showed reductions of emissions around 8.5 % (CO), 8.8 % (CO2), when it was considered 10 % of reduction in fleet composition of passenger cars and light commercial vehicles. Considering 20 % reduction in diesel fleet composition (trucks and buses), a decrease of 8.4 % (NOx) and 8.6 % (PM) was observed. Furthermore, this work presented that the kriging method to define a spatial/temporal distributing using radar traffic data is an alternative low- cost method to investigate the effect of real traffic data on the vehicular emissions modeling. This study is pioneer in Brazil and reinforced the importance of detailing traffic activities using real data to estimate vehicular emissions in an urban area. Transportation management strategies to reduce air pollution and to assist users to reduce air pollution exposure are mandatory to create a collaborative network and build sustainable cities in the future. It is necessary more investigations methods to generate an accuracy spatial distribution aggregated coupled with different traffic behavior profile to develop actions to reduce vehicular emissions in urban areas, investigate air pollution exposure, perform project-level emissions and hot-spot analysis.