Well positioned vegetation barrier (VB) have been suggested as one of the green infrastructures that could help filter particles (pollutants) from our air, thereby improving air quality. However, the filtering capacity of VB has been less well studied. A detailed knowledge of this would help in configuring VB for maximum benefit. The aim of this study is to optimize VB as a mitigating measure for worsening near-road air quality. Hence, this study made use of a Computational Fluid Dynamics (CFD) model, ENVI-met to investigate the Particle Size-removal Efficiency (PSE) of VB of different dimensions, under different wind condition. A new technique to ensure maximum benefit of VB was developed and evaluated. Preliminary results show VB has both positive and negative effects on near road air quality depending on prevailing wind condition: The so-called “positive effect” (i.e. positive PSE) due to filtration capacity can be split into two aspects i.e. VB enhances and prevents further reduction and increase of pollutants downwind respectively. Likewise, the so-called “negative effect” (i.e. negative PSE) due to blocking and aerodynamic effects of VB is also divided into two aspects i.e. VB prevents and enhances further reduction and increase in pollutants downwind respectively. Result from our new technique shows negative impact of vegetation barrier can be prevented in all cases by placing VB behind a ‘Distance of Maximum Concentration, (DMC)‘. Further investigation on the role of leeward VB on PSE of downwind VB indicates positive influence irrespective of wind parameter and barrier dimension.. Finally, recommendation was given for appropriate application of this study.

Urban green space, particularly urban forests are known to provide important ecosystem services. Improvement of air quality, especially reduction of particulate matter content of the air is among the most important services of urban vegetation. Tehran city is one of most polluted urban ecosystems of the world. This study compares five tree species (Morus alba L., Platanus orientalis L., Ulmus minor Mill., Cupressus sempervirens L. and Pinus brutia Tenore) that are commonly cultivated in Tehran megapolis for their capability to capture fine particles, particularly PM10 and PM2.5. Plant sampling was carried out during 2012 vegetative season and about 300 leaf samples were collected in 10 stations. Particulate matter content of air was obtained from air quality monitoring stations of Tehran municipality. According to our results, significant amount of particulate matter was deposited by urban woody species. The capability of tree species to capture air particles was compared statistically within and among the stations. Significant differences were found between woody species tested and their capability in different stations. We found significant correlation between particulate matter on leaf surface and different parameters including leaf surface morphological traits, cultivation pattern, concentration of particulate matter in the air and season time. All of these relationships were analyzed and discussed. Elm tree showed better capability mainly due to its rough and uneven leaf surface. There was a positive correlation between particulate matter content of air and leaf surface. We concluded that plant species, leaf morpho-functional traits, cultivation pattern along with local conditions should be considered for designing urban green space with the air refinement perspective.

Urban air pollution remains a key challenge when defining measures to reduce health impacts and for achieving sustainable development. In most cities, road transport is clearly identified as the main source of atmospheric pollutants. In spite of continuously improving vehicle efficiency standards, pollution levels have not improved in Europe as much as hoped over the last decade, due to the progressive growth in traffic levels and general urbanization (European Environment Agency, 2011). The situation will remain critical if policy measures at local, national and European level are not implemented.

In this context, urban planning might potentially be a component of air pollution mitigation strategies, due to its actions on modal choice, travel distances and dispersion of pollutant emissions in the city. Environmental approach in sustainable urban planning is however often limited to energy consumption issues, because the goals are ambitious and aim to reduce by a factor of four greenhouse gases emissions in the next 40 years. To deal with energy consumption issues, a compact city shape, based on efficient public transport and journey restrictions, is often considered as a good solution for sustainable urban development. However, the impacts of urban densification policies on air quality are not discussed, whereas the concentration of pollutant emitting activities in dense urban areas can lead to high population exposure to degraded air quality (G. Siour, 2012). The question is what are the determinants, in terms of urban layout, of a better urban air quality.

The modeling of future air quality, belonging to the field of physical chemistry of the atmosphere, is often limited to the implementation of anthropogenic emissions scenarios applied to the current urban structure, or to simple city evolution scenarios, using chemistry-transport models. These scenarios do generally not take into account the economic and energy constraints that govern the evolution of the city (size, structure around transport axes, sprawl ...) nor the urban traffic flow resulting from the balance between households budget, the supply of public transport and the urban area structure.

Here, we use an interdisciplinary four step modeling chain to analyze the effects of urban structure evolutions on air quality, using Paris urban area as a case study. We link an urban economics based transport-land use interaction model, a traffic congestion simulation model and a pollutants emission model to the chemistry-transport model CHIMERE (Siour, 2012; Menut et al, 2013). This enables to compare air pollution levels across the city in several prospective city development scenarios.