A new probabilistic analysis of air quality with risk graphs: an application in Istanbul

Abstract

In this study, spatio-temporal identification has been analyzed using new probabilistic risk graphs for air quality assessments in Istanbul, Turkiye, for the first time. Detailed assessments can be conducted through the proposed method, which is based on probabilistic models. These models contribute to the objective explanation of variations in air quality. Air quality and its fluctuations have been elucidated using risk graphs across various districts in Istanbul. According to the model results, the air quality at Mecidiyekoy and Goztepe is worse than in the other districts. Conversely, Sile and Sultanbeyli on the Asian side, as well as Sariyer and Maslak on the European side, exhibit the best air quality in terms of particulate matter (PM10) and NO2 model results. The proposed methodology provides air quality levels at different risk levels, enabling the tracking of temporal variations in air pollution risks.