Abstract
In this work, zones with high and low air pollution were determined by passive bio-monitoring. Four classes of zones were defined, which differ in the degree of pollution. In these zones, spectral data from mulberry and linden leaves were collected. It was found that their spectral indices, reduced to three principal components using Principal Component Analysis (PCA), reflect the different levels of pollution. The relationship between the spectral indices of the leaves and the degree of pollution in the considered zones was proven using the Silhouette Method - a classification assessment technique based on cluster analysis. The present study demonstrates the possibility of passively assessing air quality based on the condition of the leaves of trees grown in urban conditions. The results obtained will support the development of continuous monitoring programs in order to control pollution and its effects.