The estimation of PM₁₀ health effects and air quality forecasting plays an essential role in protecting public health against harmful air pollutants. This study aimed to estimate the impact of meteorological parameters on PM₁₀, evaluate its health impacts, and its prediction using an artificial neural network (ANN) in Yasuj. Demographic, meteorological, and PM₁₀ data were collected from March 2013 to March 2018 in one of Iran's cities. The health impacts of PM₁₀ were estimated using the AirQ+ software. Furthermore, the daily average of PM₁₀ concentrations combined with the meteorological data was used to predict PM₁₀ concentration. The results showed a greater risk of respiratory symptoms for the incidence of asthma symptoms in asthmatic children, the prevalence of bronchitis in children, incidence of chronic bronchitis in adults, and postneonatal infant mortality due to exposure to PM₁₀ with a relative risk of 1.028, 1.08, 1.117, and 1.04 respectively. Also, the best MLP-ANN model predicted PM₁₀ value with correlation coefficient (R²) of 0.87. It can be concluded that decreased PM₁₀ levels were associated with reduced symptoms of bronchitis and asthma in children and bronchitis in adults, and ANN modeling provides a feasible procedure for managerial planning in the view of air pollution.

PM ₁₀健康影响的估计和空气质量预测在保护公众健康免受有害空气污染物的侵害方面起着至关重要的作用。本研究旨在估计气象参数对 PM _{10 的}影响，评估其健康影响，并使用 Yasuj 的人工神经网络 (ANN) 进行预测。2013 年 3 月至 2018 年 3 月在伊朗的一个城市收集了人口统计、气象和 PM ₁₀数据。PM ₁₀对健康的影响是使用 AirQ+ 软件估算的。此外，PM ₁₀浓度的日平均值结合气象数据用于预测 PM ₁₀专注。结果显示，哮喘儿童哮喘症状的发病率、儿童支气管炎的患病率、成人慢性支气管炎的发病率以及因暴露于 PM ₁₀而导致的新生儿死亡的呼吸道症状风险更大，相对风险为 1.028，分别为 1.08、1.117 和 1.04。此外，最好的 MLP-ANN 模型预测 PM ₁₀值，相关系数 (R ² ) 为 0.87。可以得出结论，PM ₁₀水平降低与儿童支气管炎和哮喘症状的减轻以及成人支气管炎症状的减轻有关，ANN 模型为空气污染的管理规划提供了可行的程序。