
Abstract
Air pollution is a significant global problem, particularly in the Kurdistan region due to rapid urbanization, industrial activities, and vehicle emissions. This study aimed to measure indoor and outdoor SO2 and NO2 levels during summer and winter, predict indoor SO2 concentrations using air quality models, and assess health risks through biomarker analysis. It also evaluated the carcinogenic and non-carcinogenic effects of heavy metals, SO2, and NO2. This study was conducted at two sites: Tymar Village, an industrial area with high factory activity, and Haji Wsu Village, a non-industrial area.
The concentrations of SO2 and NO2 were measured indoors and outdoors using passive samplers at the Tymar site (20 homes) and Haji Wsu site (15 homes) in the summer and the winter. The results showed that the Tymar site had higher and more significant mean concentrations of SO2 and NO2 indoors and outdoors in both summer and winter seasons, compared to Haji Wsu site. During the summer, the mean outdoor concentrations of SO2 were the highest at both the Tymar and Haji Wsu sites, with values of 53.103 µg/m³ and 18.198 µg/m³, respectively. In contrast, the highest mean indoor concentrations of NO2 were recorded during the winter season at both sites, with values of 41.57 µg/m³ at the Tymar site and 30.16 µg/m³ at the Haji Wsu site. The indoor/outdoor ratio for NO2 was greater than one in winter in both villages.
The performance of machine learning (ML) approaches: Multiple Linear Regression (MLR), Artificial Neural Network (ANN), and Random Forest (RF), were compared in predicting indoor SO2 concentrations in both the industrial and non-industrial areas. Factor Analysis (FA) was conducted on different indoor and outdoor meteorological and air quality parameters, and the resulting factors were employed as inputs to train the models. Cross-validation was applied to ensure reliable and robust model evaluation. RF showed the best predictive ability in the prediction of indoor SO2 for the training set, with a Root Mean Squared Error (RMSE) of 2.108, a Mean Absolute Error (MAE) of 1.780, and a coefficient of determination (R²) of 0.956 and for the unseen test set (RMSE = 4.469, MAE = 3.728, and R2 = 0.779) values compared to other studied models. As a result, it was observed that the RF model could successfully be used to approach the nonlinear relationship between indoor SO2 and input parameters.
Hydroxyproline, MDA, creatinine, and albumin were measured in urine samples at both sites. The study employed a cross-sectional design with 90 participants. Tymar site had 56 participants (42 adults, 14 children), while Haji Wsu site had 34 participants (23 adults, 11 children). The Tymar site showed higher mean urinary hydroxyproline levels (66.02 µmol/L for adults, 65.57 µmol/L for children) compared to the Haji Wsu site (64.00 µmol/L for adults, 61.60 µmol/L for children), with a significant difference between the two sites. The mean MDA concentration was higher at the Tymar site (1.534 µmol/L for adults, 1.675 µmol/L for children) compared to the Haji Wsu site (1.325 µmol/L for adults, 1.162 µmol/L for children), with a significant difference between the two sites.
Dust samples were collected during July, August, and September 2021 to analyze health hazards, both carcinogenic and non-carcinogenic, for various elements (Iron (Fe), Copper (Cu), Manganese (Mn), Nickle (Ni), Chromium (Cr), Zinc (Zn), Arsenic (As), Lead (Pb), Cobalt (Co), and Cadmium (Cd)) at both sites. The results indicated that the hazard index (HI) values for all elements were below one at both sites for both children and adults, except for Cr and As at the Tymar site for children (3.85E+00 for As and 2.68E+00 for Cr) and adults (1.03E+00 for As and 1.55E+00 for Cr). The carcinogenic risk (CR) values for As, Cr, Cd, and Ni exceeded the 10⁻⁴–10⁻⁶ range, indicating no significant carcinogenic risk in the studied areas. The Hazard Quotient (HQ) values for NO2 and SO2 were mostly below one, except for indoor winter NO2 exposure at Tymar (children and adults) and Haji Wsu (children).