Tooba Alizadeh, Majid Rezaei Banafsheh, Hashem Rostamzadeh, Gholamreza Goodarzi, Hedar Maleki, Hamzeh Alizadeh,
Volume 24, Issue 74 (9-2024)
Abstract
The aim of this study was to identify the epicenter and co-occurrence factors of dust storm wave from 1 to 3 November 2017 in Kermanshah. To investigate the synoptic conditions of the causes of this phenomenon, from the European Central Center (ESMWF) mid-term weather forecast data set with a resolution of 0.125 degrees of arc including, geopotential height, omega, sea level pressure, orbital and meridional components, humidity. The Lagrangian method of HYSPLIT model was used to orient the source of dust particles. in this study, dust storm WRF-chem was simulated using a paired numerical weather forecasting model. Finally, through the processing of MODIS satellite images, its scope was determined. Examination of HYSPLIT tracking maps shows that two general paths for dust transfer to the area can be identified. 1- The northwest-southeast route, which passes through dust cores formed in the deserts of Iraq and Syria, transports dust to the western half of Iran. 2- Southwest to west of Iran and Kermanshah, which is the main source of dust on November 2 and 3, The source of the particles is Kuwait, northern Saudi Arabia and part of Iraq. The spatial distribution of the dust interpreted by the MODIS sensor images is consistent with the spatial distribution of the dust concentration simulated by the WRF-chem model.
Toba Alizadeheh, Majid Rezaie Banafsh, Gholamreza Goodarzi, Hashem Rostamzadeh,
Volume 25, Issue 78 (9-2025)
Abstract
Dust is a phenomenon with significant environmental impacts across various aspects of human life, including agriculture, economy, health, and more. The purpose of this study is to investigate and predict the dust phenomenon in Kermanshah. Meteorological data with a 3-hour resolution for the statistical period (2000–2020) from the Kermanshah station was obtained from the Meteorological Organization. First, the dust data were normalized, and then Artificial Neural Network (ANN) models were used to predict dust concentration, while the Adaptive Neuro-Fuzzy Inference System (ANFIS) was employed to analyze and predict the time series of dust occurrence in MATLAB software. The findings revealed that the maximum predicted dust concentration, related to the minimum dew point with the highest Pearson correlation with dust, was estimated at 3451.23 µg/m³. Additionally, the results of the time series prediction using the ANFIS model showed that the linear bell membership function with grade 3, during both the training and testing stages, was the most effective input function among other membership functions. According to the forecasting models, the highest probability of maximum dust occurrence in the next 20 years in Kermanshah is 94%. Based on the aforementioned studies, sufficient information was gathered to conduct this research. The phenomenon of dust, particularly in western Iran and the city of Kermanshah, has consistently posed significant challenges for the residents of these areas. This phenomenon is influenced by specific atmospheric conditions that cause irreparable damage annually, leading to respiratory issues and deteriorating air quality. Therefore, it is essential to pay serious attention to the issue of dust.
