Case Study: The Corredor Bartolomé Mitre

The following methodology of analysis, proposed in Zellner (1995) and Zellner et al. (1996), allows the identification of points of greater risk of concentration of pollutants  on one hand, and of greater potential concentration of pollutants associated to gasoline on the other.

We used a sample area called Corridor Bartolomé Mitre (ATAM, 1994), lying between the Avenues Corrientes, Leandro N. Alem, Paseo Colón, Belgrano, Jujuy and Pueyrredón (Figure 2) .

Risk Indices for the Corridor Bartolomé Mitre

The urban configuration of the area of the Corridor Bartolomé Mitre was studied in a map of scale 1:10,000 elaborated by the company Sistemas Catastrales S.A. (Figure 2) , where the average height of each block is shown in different colours.

The unit of study is the urban space defined in each intersection of streets, and the height considered is the average of the two blocks and the width of the corresponding street that produce it (Figure 1A) . The urban space defined in this way is called arch. Each arch is characterised by the average height of the two blocks that compose it, according to the colours assigned to each of them in Figure 2. The width of the streets was measured to scale for each arch.

From the data provided by Mazzeo and Venegas (1993), we calculated a weighted average of the predominant wind direction with persistence of atmospheric stability. In the analysed cases, the predominant wind direction was SSE (11,8% of the cases for periods of 3 consecutive hours of persistence and 24% for periods of 8 consecutive hours). This situation is assumed uniform and with generalised influence over the whole city (and therefore, for the whole Corridor), and it was used for the calculation of indices of ventilation. In order to elaborate a ventilation index, we estimated the alignment of the street relative to the predominant wind direction, where maximum ventilation occurs when a street has a SSE orientation, and minimum ventilation occurs when a street has the perpendicular direction (Figure 1B to 1D) . The cardinal orientation of the streets was measured in degrees in a cadastre map and a value of ventilation for each one was calculated and assigned to each arch.

The heterogeneity of heights increases the generation of turbulence (and therefore the dilution of pollutants in the air), for which we considered that the arch formed by blocks of equal average height has a greater risk than those that have different heights; and, of these, the one which presents minor risk is the one whose lower block is the one facing the wind. This was represented with a factor of heterogeneity (Fh), an integer whose value ranges from 1, for the first case, to 3, for the last.

With all this information, we created the following risk index for each arch in the Corridor Bartolomé Mitre:

 

Here, the height of the lowest block defines a minimum risk of concentration of pollutants. The minimum height was added to the average height of blocks because we assumed that it is the lower limit of risk that we might expect in an arch. Multiplication by 100 only serves for better visualisation of the results.

This index was applied to each arch in the Corridor Bartolomé Mitre. As it was previously exposed, these values are only representative in comparative terms. In Figure 3 , we plotted the icons of size proportional to the corresponding values for each arch.

Pollution Indices for the Corridor Bartolomé Mitre

For data on traffic flow, the information we used was generated by a model used by researchers of ATAM (Transportation Authorities in the Metropolitan Area), through which they calculated the vehicular volume in each arch of the Corridor Bartolomé Mitre. This model was applied only to private cars, i.e. neither taxi-cabs nor buses were included. We assumed that the flow of private cars is a valid indicator of the levels of emission because the model from which these data were obtained was based on points of greater attraction of trips. Therefore, we estimated that the taxis would circulate with greater frequency through those points and that the buses through those points would necessarily going to have higher frequencies of service. In Figure 4 we plotted the relative values for traffic flow.

The pollution indices  were calculated combining a risk factor with a pollutant emission factor. To obtain this, we multiplied the values for IR_BM calculated previously with those of traffic flow for private cars provided by ATAM. We assumed that the greater the traffic flow, the greater the amount of emission sources and, therefore, of emitted pollutants. The values for the relative indices of pollution were plotted in Figure 5 .

Discussion

This model could be applied to different meteorological scenarios, where the variation of the different risks in relationship to other atmospheric conditions could be analysed. In addition, updated information could be incorporated of other modes of traffic (buses and taxis), in order to make a characterisation of the potential pollution per type of automotive transportation, given that each mode generates different types and concentrations of pollutants.

We elaborated a methodology of analysis for a level of detail that permits the detection of sensitive or critical points in terms of concentration of pollutants in the urban spaces. This methodology could be applied to the whole city, with the purpose of identifying areas by grouping points of equal level of risk and of potential pollution.

This methodology can incorporate other variables that have not been considered, like for example, the effect of the urban "forestation" and its aggregation on the auto-purification of air. Nevertheless, the methodology that we have developed allows its application to urban planning, in the elaboration of measures such as traffic management and design, green areas requirements, emergency plans for leakage of hazardous gases, building codes, location and permitting of industrial installations or other activities, with the objective of improving the quality of our resources.

References

ATAM; november 1994. Utilización de Sistemas de Información Geográfica en el Area del Transporte. Presentado en el VII Congreso Latinoamericano de Transporte Público y Urbano, Buenos Aires, Argentina.

MAZZEO, N. A.; VENEGAS, L. E.; 1993. Normas legales y modelos de calidad de aire. 8a Reunión técnica de desarrollo tecnológico y tecnologías apropiadas para el saneamiento y medio ambiente, Mar del Plata, Argentina.

ZELLNER, M; 1995. Identificación de Areas de Riesgo de Contaminación Atmosférica en la Ciudad de Buenos Aires. Seminario de Licenciatura, Universidad C.A.E.C.E., Buenos Aires.

ZELLNER, M; CAPURRO, A. F. ; JANKILEVICH, S. S. ; 1996. Identificación de Areas de Riesgo de Contaminación Atmosférica en la Ciudad de Buenos Aires. Serie Programa de Investigación y Desarrollo Ambiental Nº 10, Universidad de Belgrano, Buenos Aires.