Title: Classification and analysing air quality with machine learning algorithms: a case study on the 2023 Kahramanmaraş earthquake

Authors: Cemal Aktürk; Tarik Talan; Adem Korkmaz

Addresses: Department of Computer Engineering, Faculty of Engineering and Natural Sciences, Gaziantep Islam Science and Technology University, Gaziantep, Turkey ' Department of Computer Engineering, Faculty of Engineering and Natural Sciences, Gaziantep Islam Science and Technology University, Gaziantep, Turkey ' Department of Computer Technologies, Gönen Vocational School, Bandırma Onyedi Eylül University, Bandırma, Turkey

Abstract: Air pollution is a danger that negatively affects all ecosystems on a global scale. One of the methods used to reveal this danger with numerical data is the air quality index (AQI). AQI allows the classification of air pollution by calculations made according to the concentration of pollutants in the air. The aim of the study is to estimate AQI with machine learning methods in order to estimate air pollution. For this purpose, air gas data of the Kahramanmaraş region of Turkey were analysed. The algorithms provided an estimation accuracy between 91% and 99%.

Keywords: air quality; air quality index; AQI; machine learning; artificial intelligence.

DOI: 10.1504/IJGW.2025.146265

International Journal of Global Warming, 2025 Vol.36 No.2, pp.107 - 116

Received: 03 Sep 2024
Accepted: 21 Dec 2024
Published online: 14 May 2025 *

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