WIT Press


Effects Of Road Traffic Scenarios On Human Exposure To Air Pollution

Price

Free (open access)

Volume

123

Pages

12

Page Range

89 - 100

Published

2009

Size

780 kb

Paper DOI

10.2495/AIR090081

Copyright

WIT Press

Author(s)

C. Borrego, A. M. Costa, R. Tavares, M. Lopes, J. Valente, J. H. Amorim, A. I. Miranda, I. Ribeiro & E. Sá

Abstract

Human exposure to air pollution has been identified as a major problem due to its known impact on human health. Particulate matter is a pollutant which rises special concern due to the adverse health effects on sensitive groups of the population, such as asthmatic children. This study is part of the SaudAr research project which main objective was to assess the air quality effects on the health of a population group risk (asthmatic school children) living in an urban area (Viseu). The aim of this paper is to investigate the influence of road traffic emissions on air quality and consequently, on human exposure. For this purpose, the CFD model VADIS integrating an exposure module has been applied over the town of Viseu, for the periods of one week in winter and one week in summer, to four different situations: the reference year (2006) and three future scenarios for the year 2030, BAU, Green and Grey scenario. The differences among the scenarios include changes on the existing land use, the vehicle fleet composition, the mobility, the vehicle technologies and the fuel types. Field campaigns were performed in order to obtain information about vehicle fleet in the town of Viseu and mobility patterns. The quantification of road traffic emissions and the hourly traffic emissions patterns for all scenarios was carried out by the application of the TREM model. The results reveal an increase in PM10 emissions, concentrations and exposure in all future scenarios, particularly in winter with an increase around 80% in the BAU and Grey scenarios and only 34% in the Green scenario. Keywords: traffic emissions, air quality modelling, human exposure, development scenarios.

Keywords

traffic emissions, air quality modelling, human exposure, development scenarios