The aim of the study was to rank and classify Hungarian cities and counties according to their
environmental quality and level of environmental awareness. Ranking of the Hungarian cities and
counties are represented on their „Green Cities Index” and „Green Counties Index” values. According
to the methodology shown in Part 1, ci
techniques and efficacy of the classification was analysed. However, they did not give acceptable
results either for the cities, or for the counties. According to the parameters of the here mentioned
three algorithms, reasonable structures were not found in any clustering. Clusters received applying
algorithm fanny, though having weak structure, indicate large and definite regions in Hungary, which
can be circumscribed by clear geographical objects.
Human health is essentially influenced by air quality. Atmospheric air in residential areas contains
many pollutants. The monitoring and the plain publishing of the measured values are important both
for the authorities and the public. Air quality is often characterized by constructing air quality indices,
and these indices are used to
usually done by averaging the measured data usually in time and space; hereby important aspects of
the data can be lost. All known indices contain only chemical pollutants, while certain biological
pollutants can enhance the effects of the chemical pollutants and vice versa. In this paper we discuss
the importance of integrating biological pollutants into air quality indices. In order to increase
efficacy of these indices to the civil society we aim to introduce geographic information system (GIS)
methods into publishing air quality information.
This paper determines the characteristic weather types over the Carpathian Basin for the summer –
early autumn period (July 15 – October 15) and the winter months (December, January, and
February), with the levels of chemical (CO, NO, NO2 , NO2/NO, O3, O3max, SO2, PM10) and biological
[Ambrosia (ragweed) pollen] air pollutants, and
the ECMWF data set, daily sea-level pressure fields analysed at 00 UTC (Coordinated Universal
Time) were prepared for each weather type (cluster) in order to detect the relation between, on the one
hand, the sea-level pressure patterns and, on the other, the levels of the chemical and biological air
pollutants as well as the frequency of the respiratory diseases in Szeged. Objective definition of the
characteristic weather types occurred by using the methods of Factor Analysis and Cluster Analysis.
As a result, in the summer – early autumn period the total patient number is proportional to the mean
monthly temperature, the maximum and minimum temperatures; however, respiratory diseases occur
more frequently, when relative humidity is low. On the other hand, in the winter months there is no
relation between the meteorological variables and the patient numbers.