Air Quality Model Regional Ozone Street Canyon Indicator Data Scenario Comparaison

VADIS - Street Canyon Results

Domain definition

 

The domain defined for VADIS application for each city is presented in Figure 3.3.1, which includes a brief description of each domain (dimension, grid resolution, number of buildings and number of sources).

 

 

 

Figure 3.3.1 – VADIS domains and main characteristics.

 

The area chosen for the street-level dispersion model is one of the major road connecting the Genoa centre and the western coastal part with the belt motorway surrounding the northern part of the city. The domain was selected because of its geometrical properties and of its intense traffic conditions, which comprehend also of a consistent flow of heavy duty vehicles and trucks directed towards the fruit market during the night and the early morning. Figure 3.3.2 represents the location of the domain in Genoa.

 

Figure 3.3.2 Location of TREM domain in Genoa

 

 

The  VADIS domain defined in Geneva city centre is located in the city downtown near Rhône River (see Figure 3.3.3). The choice of the domain was been guided by the followings reasons: presence of an air pollution measurement station, hot spot with heavy traffic emissions and centre of the city.

 

Figure 3.3.3 Location of VADIS domain in Geneva

 

 

The domain defined in Lisbon city centre is located in the city downtown near Tagus River, between Terreiro do Paço and Rossio, spots of special touristic interest. As represented on Figure 3.3.4 (the simulation domain is represented by the black rectangle), a cluster of rectilinear buildings and perpendicular streets characterise this area. This residential and commercial area comprehends several one-way roads with an intense flux of traffic and a pedestrian zone, where local hot-spot air pollutants levels are expected to occur.

 

Figure 3.3.4 Lisbon downtown cartographic map (scale 1:7016) and simulation domain.

 

In Tel Aviv the VADIS model has been run for Allenby Street, located in the south of the city centre (see Figure 3.3.5). It was chosen as it represents typical street canyon features and has a monitoring station located close to enable validation of results.

 


Figure 3.3.5 Location of VADIS domain in Tel Aviv

 

VADIS was applied to a specific hot spot area in the centre of Thessaloniki (see Figure 3.3.6), where high air pollutants levels are expected to occur because of heavy traffic emissions. It is a highly commercial area located in the centre of the city.

Figure 3.3.6 Location of VADIS domain in Thessaloniki

 

Input data description

 

The buildings and emission sources coordinates definition, the meteorological conditions description and the CO, NOx and PM10 emissions characterization, constitute the main VADIS input data.

 

§      Buildings Volumetry

 

Geneva: A very precise digital elevation model provided height value for every square meter with a precision of 30 to 40 centimetres. The data acquisition method was done by laser interferometer from an helicopter.

 

Lisbon: Downtown buildings form an homogeneous block of 26 rectangular buildings, all with the height of 15 m. To simplify the obstacles definition process, and as all of the 26 buildings have a 344º orientation, the cartographic grid was rotated according with this alignment.



Figure 3.3.7 Simulation domain 3D perspective

 

 

§      Meteorological data

 

Meteorological input data includes: wind speed, wind direction and temperature. VADIS model simulations were performed for the:

  • Geneva: 13th and 26th January 2001;
  • Genoa: 24th April 2001;
  • Lisbon: 8th July 1997, a typical summer day chosen using a statistical meteorological approach;
  • Tel Aviv: 18th October 1998;
  • Thessaloniki: 9th September 1998.

 

As an example, Figure 3.3.8 shows the wind direction during the simulation day for Lisbon.

Figure 3.3.8 Wind velocity and direction hourly variation for the 8th of July.

 

§      Emissions data

 

The hourly traffic emissions data were estimated using the Transport Emission Model for Line Sources (TREM -described in detail on EC SUTRA Project Technical Report D04.1. (TREM, 2002). The numerical system TREM/VADIS was developed towards the estimation of the atmospheric pollution induced by road traffic in urban areas.

 

Simulation results and analysis

Lisbon: The wind and CO dispersion fields were simulated with VADIS for the 6 p.m. of July the 8th, as presented in Figure 3.3.9. From 6 p.m. simulation results presented on figure 14 it is possible to notice higher CO concentration values located in Prata street and adjacent pedestrian streets.

 

Figure 3.3.9 The wind and CO dispersion fields were simulated with VADIS for the 6 p.m. of July the 8th(location of the air quality station).

 

 

Thessaloniki: The CO concentration field for a traffic rush hour with specific dispersion conditions were calculated. Figure 3.3.10  shows the wind and concentration fields obtained with the VADIS model.

 

 

 

Figure 3.3.10 CO dispersion simulation for Thessaloniki for 7 a.m. of  9 September 1998.

 

Tel Aviv:Figure 3.3.11 shows, for both NOx and CO, high concentrations at three points in the centre of the street.

 

 

Figure 3.3.11 NOx and CO dispersion simulation for Tel Aviv for 6 p.m.


The produced indicators

VADIS results allowed the determination of following state indicators:

§         NOx peak concentration (mg/m3)

§         CO peak concentration (mg/m3)

§         PM10 peak concentration (mg/m3).

 

Lisbon:

§         CO peak concentration (mg/m3): 17830

§         NOx peak concentration (mg/m3): 1194,1

§         PM10 peak concentration (mg/m3): 55,6

 


Simulation results and analysis

Considering the city scenarios, the local scale model VADIS was applied to the same simulation domain of the baseline scenario and with identical meteorological conditions. The traffic emissions resulting from the VISUM/TREM cascade for city scenarios application was used in order to perform the air quality simulations.

 

Results of the Common Scenarios are represented in the following figures

 

*    GENOA

 

§        CS1: Young and virtuous

 

 

Figure 4.2.1 Genoa wind and CO dispersion fields for CS 1.

 

 

Table 4.2.1 Maximum values of concentration for CO for CS1.

Definition

Value (mg/m3)

Maximum value calculated on the domain:

11.33

95-th percentile

1.08

Air quality limit defined by Italian law

10.00 (on a 8 hrs average)

 

§        CS2: Young and vicious

 

Figure 4.2.2 Genoa wind and CO dispersion fields for CS 2.

 

 

Table 4.2.2 Maximum values of concentration for CO, for CS2.

Definition

Value (mg/m3)

Maximum value calculated on the domain:

44.58

95-th percentile

4.38

Air quality limit defined by Italian law

10.00 (on a 8 hrs average)

 

 

 

§        CS3: Old and virtuous

 

Figure 4.2.3 Genoa wind and CO dispersion fields for CS 3.

 

 

Table 4.2.3 Maximum values of concentration for CO, for CS3.

Definition

Value (mg/m3)

Maximum value calculated on the domain:

5.64

95-th percentile

0.530

Air quality limit defined by Italian law

10.00 (on a 8 hrs average)

 

§        CS4: old and vicious

 

Figure 4.2.4 Genoa wind and CO dispersion fields for CS 4.

 

 

Table 4.2.4 Maximum values of concentration for CO, for CS4.

Definition

Value (mg/m3)

Maximum value calculated on the domain:

14.41

95-th percentile

1.36

Air quality limit defined by Italian law

10.00 (on a 8 hrs average)

 

 

*    LISBON

 

§        CS1: Young and virtuous

 

Figure 4.2.5 Lisbon wind and CO dispersion fields for CS 1.

 

§        CS2: Young and vicious

Figure 4.2.6 Lisbon wind and CO dispersion fields for CS 2.

 

 

§        CS3: Old and virtuous

Figure 4.2.7 Lisbon wind and CO dispersion fields for CS 3.

 

 

§        CS1: old and vicious

Figure 4.2.8 Lisbon wind and CO dispersion fields for CS 4.

The analysis of the state indicators for VADIS model for the reference situation and city scenarios in Lisbon application shows an increase of CO, NOx and PM10 concentrations for scenario 2 relatively to the baseline scenario. This situation can be related to the raise of the number of trips and the consequently increase of traffic emissions in a young and vicious city. In scenarios 1 and 3 the peak concentration determined in the simulation domain for each pollutant is lower than the one verified for the reference situation. The scenario 4 presents a similar behavior to the one verified in the actual situation.

 

 

Figure 4.2.9 State indicators of the reference situation and city scenarios for the Lisbon application.

 

Table 4.2.10 State indicators for Lisbon City scenarios application.

 

SC1

SC2

SC3

SC4

CO peak concentration (mg/m3)

7831,19

39305

6294,77

15161

NOx peak concentration (mg/m3)

470,4

2640

564

1058,6

PM10 peak concentration (mg/m3)

33,3

140,05

23,95

52,51

 

 

 

 


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