Volume 8 [2006]

Urban air quality nowadays is one of the major environmental issues, due to its impact to
various health problems, caused by the daily exposure of the population in dangerous air
pollutants. The highest levels of air pollutants are usually observed in street canyons, emitted
by urban traffic. To understand the way that pollutants dispersed in a street canyon
environment, various modeling techniques are used. Both the accuracy of the predictions and
the quickness of the calculations, are significant factors to adopt a modeling technique.
In the present study, we used benzene as an indicator of traffic pollution. Two different
modeling techniques, an artificial neural network (ANN) and a semi empirical deterministic
model (DET) are used, to predict benzene concentrations in a street canyon environment.
The ANN was based on a training procedure using measurements collected in a specific
street canyon (benzene concentrations, traffic density, vehicle’s type distribution), while the
DET model was based on road traffic emission rate, wind speed and direction, and the
geometrical characteristics of the road.
After the validation of models, their response to preselected “what if” scenarios was
attempted.
Although both models produced very good results, given the limited amount of data available,
the ANN succeeded slightly better than DET in predicting benzene concentrations. On the
contrary, ANN presents lower response in predicting the effect of significant changes in traffic
flow patterns on benzene concentrations.
The results from the simulations indicate that the ANN is a promising technique for benzene
modeling in an urban environment, since DET seems to be ideal for environmental
management purposes.

In this paper, we present the estimate and results of measurement of air pollution in Béjaia
city in Algeria.
We used an enclosure of 0,80 m3 for the collection of gases directly on the outlet side of the
tailpipe of the vehicles. A three-gas detector (MX21 plus), introduced inside the enclosure,
measures the rates of carbon monoxide CO, sulphur dioxide SO2 and nitric monoxide NO. We
studied the exhaust pollutants according to the age of the vehicle (1980 – 2004) and the
acceleration of the engine. Measurements related to a sample of 204 vehicles using gasoline
or diesel oil fuel.
The comparison between the rejections and the standards European, American and
Japanese norms encourages us to challenge the authorities on the urgency of the
introduction of the vehicle inspection and technical control. Except the new vehicles (less than
5 years old), where the results are comparable, the others exceed largely the standards.
We have counted the number of vehicles passing through the Daouadji square during one
month (March 2004) and calculated the total pollution rejected. The comparison with the air
pollution measured in situ confirmed that urban pollution is primarily from automobile sources.
On the curve of the weekly evolution of the air pollution the days and peak hours of the
automobile traffic appear clearly. The correlation with the number of vehicles is very
significant (0,78).
By taking account of the annual rate of increase in the number of vehicles and keeping the
current park without adequate maintenance, a statistical model envisages an unbearable
urban pollution near 2010.

The EU Directives and legislation by worldwide environmental authorities impose constantly
lower levels for the airborne pollutant emissions of internal combustion engines towards the
goal of zero emission vehicles. During the last decade, engine manufacturers, refiners and
fuel companies invest highly in order to comply with the increasingly severe emission
requirements.
The diesel engine is widely used for transportation, manufacture, power generation,
construction and farming operations. There are different kinds of diesel engine depending on
their application: small, high speed, indirect-injection engines or low speed, direct -injection
behemoths with cylinders more than one meter in diameter. Their main advantages are the
efficiency, economy and reliability. The physicochemical properties of the diesel fuels and the
engine design affect the operability, the efficiency and the performance of the diesel engine
and they correlate to the exhaust emissions.
In Greece, the diesel fuel market steadily increases during the last years. The fuels produced
by the refineries usually comply with the existing specifications. However, alterations in the
fuel properties may occur through the supply chain to the service stations due to failures of
the distribution system (i.e. contamination with water, tank sludge and residues) or
adulteration with lower value and taxation fuels (heating oil, marine diesel or industrial
solvents).
The transportation sector is a major source of air pollution. It contributes to harmful exhaust
emissions, such as greenhouse gas emissions, carbon monoxide, sulfur oxides (SOx),
nitrogen oxides (ΝΟx), unburned hydrocarbons (HC) and particulate matter (PM) emissions.
In this paper, PM and exhaust emissions from a stationary single cylinder diesel engine were
examined. For comparison purposes, tests were carried out with a typical automotive diesel
fuel of the Greek market and with adulterated fuels with heating oil or white spirit. The noncomplying
diesel fuels gave increased emissions in all cases with only exception the PM
emissions due to adulteration with white spirit. More specifically, the experimental results for
the adulterated fuels with heating diesel showed an increase of the nitrogen oxide emissions
up to 73.9%, of the unburned hydrocarbons up to 29.6% and of PM up to 121% compared to
the baseline diesel fuel emissions.

The paper describes the development of a fast and easy-to-use qualitative tool for preliminary
assessments of urban air quality related to road traffic. The tool is particularly aimed at the
ability and budget of local government. It uses a novel interaction matrix-type methodology
combined with mapping overlay, performed via a GIS. More specifically, the interaction matrix
provides the weighting factors, which show the impact of each variable involved in a system
on the target variable, air quality, as well as on the system as a whole. These weighting
factors are used in the GIS to produce vulnerability maps. The maps visualise vulnerability to
air pollution due to the combined effect of a number of interacting factors, and thus indicate
areas susceptible to poor air quality. This results in a considerable reduction in computing
time and complexity compared to the use of a sophisticated numerical model, as the user of
the GIS tool only needs to perform mapping overlays in the GIS (using the previously derived
weighting factors).
The particular aim of this study was to compare two different methods for quantifying the
interactions between variables in the matrix. The first method used constant coefficients,
whose values are based on parametric studies performed using an advanced dispersion
model or on good engineering judgement. The second method used a more sophisticated and
versatile quantification of the interactions between variables, via analytical or semi-empirical
relationships. In the latter method, the matrix was formulated computationally, so that the
interaction weightings for different conditions can be obtained automatically.
The technique was applied to the case study of an urban area with a high traffic throughput, in
the UK. Two different interaction matrices were constructed for urban air quality linked to road
traffic, based on the above methods. The GIS results based on both matrix methodologies
were compared to the results of a more intensive dispersion numerical model in terms of
pollutant dispersion patterns and hot spots. Both sets of results were shown to compare
favourably with those of the numerical model. The results based on the more sophisticated
matrix coding were found to be in closer agreement with those of the numerical model.