Table 1.
Value ranges of AQI and corresponding health warnings.
Table 2.
Summary of studies applying machine learning models to predict the AQI.
Fig 1.
Location map of the study area and flowchart of the methodology.
The study area is located in Iğdır Province, Türkiye. The base map is sourced from Natural Earth (public domain; http://www.naturalearthdata.com) and elevation data are from the USGS National Map Viewer (public domain; https://www.usgs.gov).
Table 3.
Reference intervals used in AQI calculation.
Table 4.
Annual air pollutant and metrological factor dataset.
Fig 2.
Correlation matrix for response and explanatory variables.
Fig 3.
Optimized model results with 3D surface plot (Train set).
Fig 4.
Optimized model results with 3D surface plot (Test set).
Table 5.
The goodness of fit criteria results in all algorithms for optimal hyperparameter values.
Fig 5.
Variable importance for models.
(a) XGBoost; (b) LightGBM; (c) SVM.