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Evaluation of Transport Systems

发布时间:2018-01-12
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The transport system plays a very important role in the economic markets and quality of citizens‟ life. It can be helpful to economic growth and employment, if it is sustainable and effective. show that Mobility has increasingly enhanced at global, European and national contexts: between 1990 and 2007 the road transport increased by 29% and car ownership has had an increase of 34% in the EU-27 (EEA, 2010). The current transport model is responsible for 23% of the energy consumed in Europe, where about three-quarters is due to the road transport (IPCC, 2007). Furthermore, it is estimated that 96% of energy used for the transport sector is based on the use of oil and its derivatives both at global and European level (IPCC, 2007; EC, 2011). As a consequence, high emissions of greenhouse gases into the atmosphere and other harmful emissions for the human health and environment are occurring (U.S. EPA, 2010).

Air pollution in urban areas is a significant problem, because it negatively affects the human health and well-being (WHO, 2005; Dandy, 2010). These effects led to the work-days losses, to increase of chronicle ills and, as a consequence, an increase of national sanitary costs (Hunt, 2011). Moreover, functional performances of urban vegetation as ecosystem services may be reduced by pollution impacts (Manes et al., 2012). CO2 emissions induced by motorised mobility should be reduced by approximately 60% by 2050 compared to the 1990‟s ones (EC, 2011). European Commission pointed out some measures at aiming to reduce traffic volumes as the increase of collective transport, integration of measures for cycling and pedestrian mobility through new re-organisation of the urban mobility system and its co-related infrastructures (EC, 2011). The reduction of both transport-related greenhouse gas emissions and urban air pollution and an increase of the walked and cycled distances have important benefits on human health (Woodcock et al., 2007).

Thinking about a possible 26 traffic reduction and amelioration of human health, it is possible to consider different types of movement for people, which can be divided on the basis of their length: proximity, short-haul, local, mid distance and long distance (ISFORT, 2011). In Municipalities with more than 250,000 inhabitants in 2011, the proximity journeys were 31.1% and those of short-haul 25.8% (Table 1). Within this extent, slow mobility (accounting for walking and cycling journeys) should have a major role, but it constituted less than 15% of the total mobility (ISFORT, 2011). Therefore, it is evident that private motorised mobility predominates in all types of journeys, although it may be with a lower percentage in the proximity and short-range movements (Table 1). However, in a range of 5 km is proved that slow mobility is more effective than motorised one (Gruber, 2012). The characteristics affecting the increase or reduction of cycling and walking mobility include: functional aspects related to the structure of settlement, destination, safety and pleasure (Pikora, 2003). The pleasantness is also related to the occurrence of parks and private gardens, and to low levels of air pollution (Burden et al., 1999; Pikora, 2003). Hawthorne (1989) emphasised the 40 importance of urban green for the occurrence of walking practices, which happen mainly in 41 parks with shadowing trees during the hottest days of the year, whereas the unappealing environmental qualities included air pollution too (Pikora, 2003).

1.2 Road network-types, permeability and access to private and public transport

The network connectivity degree can at all affect the transportation mode, energetic consumes and harmful emissions. Ewing (1996) reported finding no relationship between transit use and street network design after controlling for other variables such as urban density and facility frequency. Ewing also reported that grid-like patterns could be more friendly transit to the extent that they allowed greater penetration of an area by transit services. Ewing‟s study considered to what extent various urban features might be regarded as being essential or highly desirable in terms of contributing to pedestrian and transit design.

Among the essential characteristics were short to medium length blocks (relating to network permeability) and continuous sidewalks (relating to the connectivity of the pedestrian network), while having a grid-like street network was considered highly desirable. These examples suggest that the ability to single out the effects of road network type per se on travel behaviour may not be straightforward. However, underlying the many contingent factors, there seems to be a basic inverse relationship between the attractiveness of a mode and the distance travelled by that mode. This means that a grid layout may be associated with sustainable travel insofar as it promotes short and direct routes for pedestrians, including pedestrian access to public transport. But, by the same token, a grid may promote „unsustainable‟ travel for car traffic. Due to the great importance of the use of private car, the grid-like street network characterising compact tissues has been abandoned, favouring thus open tissues with low connectivity degree (Southworth, 2004). In recent years, several studies have been addressed to the promotion of forms of sustainable urban development, in which the shape and structure of urban areas could assist for a travel reduction (Agencia d‟Ecologia Urbana de Barcellona, 2008; Southworth, 2004; Stead and Marshall, 2001) and for increasing the slow mobility. These studies highlighted two main road typologies: the first based on the flow split of several modalities transport and the second one characterised by sharing of the public space that favours the social relationships and slow mobility. The proximity to transport networks also influences travel patterns and consequently transport energy consumption. Better access to major transport networks increases travel speeds and extends the distance, which can be covered in a fixed time. Major transport networks can be a powerful influence on the dispersal of development – both residential and employment development. Interestingly, Kitamura et al. (1997) reported that the distance from home to the nearest bus stop and railway station affected the modal share.

1.3 The role of urban forests and street trees in the air pollution removal

Urban forests can affect local and regional air quality by removing atmospheric pollutants, emissions of biogenic volatile compounds (BVOCs) from vegetation (Loreto and Schnitzler,

2010). Urban micro-climate is altered by presence of urban forests because they reduce air temperatures through shading and evapotranspiration, change wind patterns, modify boundary layer heights, and reduce the building energy use, mitigating - in short, the urban heat island phenomenon (Beckett et al., 2000; McPherson et al., 1999; Nowak et al., 1998a,b, 2006; Yang et al., 2005; Nowak and Dwyer, 2007; Schäfer et al. 2014). Urban forests also positively affect global climate change through direct removal of greenhouse gases and by affecting emissions from energy production (Parrish and Zhu, 2009). Among different functions that are attributed to the urban vegetation - aesthetic qualification, recreation, shading, water retention, etc., the ability to remove air pollutants by leaf adsorption/absorption is perhaps the least known with regard to the mechanisms (Escobedo et al., 2011). Trees and shrubs are able to intercept and retain both gaseous and particulate pollutants, which are harmful to the human health (Cheng et al., 2013; Pope et al., 2009; Hanzalova et al., 2010; Beckett et al., 1998).

Several studies have quantified the amount of air pollution removed by urban forests (Yang et al., 2005; Escobedo et al., 2011; Leung et al., 2011). Nowak et al. (2006) studied air pollution removal and air quality improvement by urban forests for several cities in the USA. Using assumed urban forest structure values such as leaf area index, estimated mean removal of PM10 by trees in Los Angeles was 8.0 g m−298 . Yang et al. (2005) debated the role of urban forests on air quality in Beijing and found that pollution removal rates by its urban forest were greater than those for cities in the United States.

The green band is considered as a strip of trees of different species growing in proximity to a pollution source, and it is assumed to be able to significantly attenuate it by means of interception and assimilation (Hunter et al., 2014). The vegetation can indirectly be a sink of gas pollutants, but it can also intercept tons of dust providing an effective and healthy barrier.

Plants remove air pollutants in three ways: 1) absorption by the leaves, 2) deposition of particulates and aerosols on the leaf surfaces, and 3) fallout of particulates from the leeward side of vegetation due to slowing of the air movement (Currie and Bass, 2008). The air pollutants removal by tree and shrub canopies is different in relation to the pollutant type: PM10 is mainly intercepted by leaf surfaces and, the presence of hairs and exudates allow to the particulate matter to be trapped and then washed away by rain. A portion (on average 50%) of PM10 will be re-suspended in the air especially after a long time period without rain, although some evidences have proven that re-suspension is extremely small to the tree canopy (Tiwary et al., 2009). The more reactive compounds, such as ozone, can interact with leaf surfaces by direct contact or enter inside throughout the stomata openings. The stomatal air pollutant uptake depends on pollutant concentration, meteorology, and plant characteristics (Zona et al., 2014). A quantitative evaluation of these processes has been object of extensive studies and now there is consensus that the green spaces represent an important component to be included in all strategies for protecting and improving air quality.

This work concerns estimation of the PM10 removal by street trees for an urbanised area located in the centre of municipality of Rome. It will be shown a methodological approach based on field data collecting and modelling to calculate some basic variables such as deposition velocity, Leaf Area Index and pollutant removal Flux. Considerations about the total PM10 removal and the role of the street trees for intercepting particulate matter will be discussed, also in relation to different 126 road typologies. Moreover, two basic assumptions concerning different deposition velocity calculations such as those proposed by Escobedo and Nowak (2009) and Yang (2005) will be also discussed.

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