A Multi-Country Statistical Analysis Covering Turkey, Slovakia, and Romania in an Educational Framework

Tugce Pekdogan, Mihaela Tinca Udriștioiu (), Silvia Puiu, Hasan Yildizhan and Martin Hruška
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Tugce Pekdogan: Department of Architecture, Faculty of Architecture and Design, Adana Alparslan Türkeş Science and Technology University, 46278 Adana, Turkey
Mihaela Tinca Udriștioiu: Department of Physics, Faculty of Sciences, University of Craiova, 200585 Craiova, Romania
Hasan Yildizhan: Department of Energy Systems Engineering, Adana Alparslan Türkeş Science and Technology University, 46278 Adana, Turkey
Martin Hruška: Faculty of Natural Sciences, Matej Bel University Banská Bystrica, 974 01 Banská Bystrica, Slovakia

Sustainability, 2023, vol. 15, issue 24, 1-16

Abstract: This paper uses hierarchical regression analysis, a statistically robust method, to explore the correlations between two meteorological parameters and three particulate matter concentrations. The dataset is provided by six sensors located in three cities from three countries, and the measurements were taken simultaneously for three months at each minute. Analyses and calculations were performed with the Statistical Package for the Social Sciences (SPSS). The results underscore that the complexity of air pollution dynamics is affected by the location even when the same type of sensors is used, and emphasize that a one-size-fits-all approach cannot effectively address air pollution. The findings are helpful from three perspectives: for education, to show how to handle and communicate a solution for local communities’ issues about air pollution; for research, to understand how easy a university can generate and analyze open-source data; and for policymakers, to design targeted interventions addressing each country’s challenges.

Keywords: particulate matters; meteorological parameters; hierarchical regression; human health; environmental education (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
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